High speed and shock compression behind the bow shock of an aircraft head result in very high temperature, which would subsequently lead to a conductivity plasma flowfield around the vehicle. The plasma gas provides a direct working environment for the application of magnetic field. The magnetohydrodynamic (MHD) flow control, which uses the magnetic field to alter the trajectory of ions or electrons, can improve the aerodynamic characteristics of hypersonic vehicles effectively. It has potential prospects on aerodynamic force control and aerodynamic heating management. Besides, the development of superconducting materials and electromagnetic technology contribute to a great upsurge of MHD flow control research significantly. Although research work has been carried out in the field of MHD flow control at home and abroad, its experimental investigation is still challenging. And for the measurement of pressure and heat flux, there is no systematic conclusion because of the limited test conditions and measurement techniques. The results of different researchers may be different from each other and from the theoretical results and numerical simulations. Thus, the influence on the shock stand-off distance, pressure and heat flux under MHD flow control deserves an in-depth investigation. Besides, the numerical simulations and theoretical methods do also need reliable experimental data for variation. The aim of this review paper is to summarize and discuss the developments on MHD flow control technology based on high temperature real gas effect, including the experimental technique, numerical method, and the influence rules and dynamics mechanism of MHD flow control. Its development trend is also discussed and prospected in the paper.
2021, 53(6): 1515-1531.
doi: 10.6052/0459-1879-21-067
Solving the Reynolds-averaged Navier-Stokes (RANS) equation remains an effective and practical approach in engineering applications, but the uncertainty of Reynolds stress modeling will lead to discrepancies in the prediction accuracy of this approach. With the development of artificial intelligence, the data-driven method of turbulence model combined with machine learning algorithm is more effective than the original RANS model, however, the stability and prediction accuracy of the data-driven method could still be further improved. In the present paper, a fully connected neural network is constructed to predict the eddy viscosity, and this neural network is called as Eddy Viscosity Neural Network (EVNN). Additionally, a tensor-based neural network (TBNN) is also applied to predict the higher-order eddy viscosity relationship between the unclosed quantity and the analytical quantity, and the basis tensors are used to ensure the Galilean invariance. Finally, the closed-loop accuracy of the predicted flow field is realized through multiple modifications. For the method above, the neural network which is combined by EVNN and TBNN, is trained by using the high-fidelity data generated by the large eddy simulation (LES) and the baseline data obtained by the RANS simulation. Compared with the high-fidelity LES results, the results of the modified model exhibit significantly higher accuracy in the posterior velocity field, the mean pressure coefficient, and the mean friction coefficient than the original RANS model. It can be found that the implicit treatment of the linear part of the Reynolds stress can enhance the numerical stability, and the modification of the nonlinear part of the Reynolds stress can better predict the anisotropic characteristics of the flow field. Furthermore, the prediction accuracy is further improved through the multiple modification strategy. Therefore, the combined neural network and multiple modification strategy developed in this paper, have strong potentials in data-driven turbulence modeling and engineering applications in the future.
2021, 53(6): 1532-1542.
doi: 10.6052/0459-1879-21-073
It is a challenging and important issue to establish a nonlinear dynamic model of system by use of limited data. The data-driven sparse identification method is an effective method developed recently to identify the governing equations of the dynamic system from data developed in recent years. In this paper, governing equations for different flows are identified by data-driven sparse identification methods. Partial differential equation functional identification of nonlinear dynamics (PDE-FIND) scheme and least absolute shrinkage and selection operator (LASSO) scheme are used to identify the governing equations of two-dimensional flow past a circular cylinder, liddriven cavity flow, Rayleigh-Bénard convection and three-dimensional turbulent channel flow. An over-complete candidate library is constructed by direct numerical simulation flow field data in the process of identification. Variables in the library are retained up to second order, variable derivatives are retained up to second order, and nonlinear terms are retained up to fourth order. By comparing the results from the two methods, we find both methods show good performance in identifying governing equation with no nonlinear terms, i.e., vorticity transport equation, heat transport equation and continuity equation. PDE-FIND scheme correctly identified the governing equations and Rayleigh number and Reynolds number for the flow field. But LASSO scheme failed to identify the governing equations which contain strong nonlinear terms, i.e., Navier-Stokes equations. This is because grouping effect may occur among the items in the candidate library and only one item in the group is chosen in such case in LASSO scheme. So PDE-FIND scheme is more effective than LASSO scheme in sparse identification of strongly nonlinear partial differential equation. It is also found that selecting data from regions with abundant flow structures can improve the accuracy of data-driven sparse identification results.
2021, 53(6): 1543-1551.
doi: 10.6052/0459-1879-21-052
STUDY ON THE SPECTRUM CHARACTERISTICS OF VORTEX-INDUCED VIBRATION OF THREE TANDEM CIRCULAR CYLINDERS
The numerical computation of vortex-induced vibration of three circular cylinders in a tandem arrangement with two degrees of freedom has been carried out. The effects of Reynolds number, natural frequency ratio and reduced velocity on the dynamic response and spectral characteristics of three tandem cylinders were analyzed. The results indicate that the Reynolds number and natural frequency ratio have little influence on the amplitude and fluid force coefficient of the upstream cylinder. The frequency locked region of the midstream cylinder increases with the increasing of Reynolds number. The dynamic response of the midstream cylinder is greatly affected by the wake of the upstream cylinder, whereas the effect of natural frequency ratio is small. Meanwhile, when the reduced velocity is small, Reynolds number and natural frequency ratio have great influence on the fluid force coefficient. In addition, the amplitude and the fluid force coefficient of the downstream cylinder are greatly affected by Reynolds number and natural frequency ratio. Reynolds number, natural frequency ratio and reduced velocity have great influence on the main peak amplitude, spectrum component and fluctuation of fluid force coefficients PSD curve. The fluctuation of the PSD curve becomes intense, giving rise to the movement trajectory of cylinder from "8" shape to irregular shape. As natural frequency ratio increases to 2.0, the P$+$S mode is found in the wake of the upstream cylinder, which leads to the occurrence of asymmetric motion, and the equality of main peaks of the PSD curve of the lift and drag coefficients. Finally, the variation of average power value of excitation load with reduced velocity is similar to that of corresponding structural dynamic response. In the same reduced velocity range, the strength of structural vibration response is directly proportional to the average power value of displacement. When analyzing the power spectral density of lift coefficient in different intervals, the vibration frequency ratio has more influence on the structural vibration response.
2021, 53(6): 1552-1568.
doi: 10.6052/0459-1879-21-036
When the computational fluid dynamics discrete element method (CFD-DEM) is used for solid-liquid two-phase coupling analysis, the selection of particle calculation time step directly affects the accuracy and efficiency of the coupling calculation. For this reason, each target particle is selected as the research object, and interpolation function is introduced to calculate the motion displacement of the time step, and a variable spatial search grid is constructed. An improved particle collision search algorithm (modified discrete element method, MDEM) was proposed by selecting possible collision particles to build a search list and using reverse search Method to judge collision particles. The algorithm in particle group and fluid coupling calculation, the particle counting the initial time step selection particle collision time without limit, realization of automatic adjustment and correction by large step, calculated by the real-time update of fluid particles and fluid coupling conditions, time step, the granular computing time step selection, as a result of low computational efficiency, selection is too large too small to solve the problem of false negatives, particle collision of particles and fluid coupling numerical simulation provides a effective calculation method. Through the numerical simulation of two particles and multiple particles, the relative errors of the collision forces, collision positions and times between particles obtained are all less than 2% compared with the theoretical calculation results. Compared with the traditional DEM collision search algorithm, the three calculation time steps selected do not affect the calculation accuracy, and the calculation efficiency is higher. Through the coupling numerical simulation of multiple particles and fluid, using the traditional CFD-DEM method, the precise solution can be obtained only when the particle calculation time step is 10$^{-6}$ s or smaller, while the precise solution can be obtained by using the proposed method to take 10$^{-4}$ s, which avoids the problem of missed decision caused by particle collision with the increase of time step, and the calculation time is reduced by 16.7%.
2021, 53(6): 1569-1585.
doi: 10.6052/0459-1879-21-002
Recently, the flux reconstruction (FR) method has attracted more and more attentions for its simplicity and generality. However, it is still computationally expensive and time consuming when simulating the complex flow problems by FR method. There is a huge demand for developing appropriate efficient implicit solvers and parallel computing techniques for FR. This paper proposes an implicit high-order flux reconstruction solver on GPU platform based on the block Jacobi iteration method. As it is inefficient to solve the large global linear system resulting from spatial and implicit temporal discretization of FR directly. A block Jacobi approach is used to change the characteristics of the lift-hand matrix of the global linear system and this avoids the dependence of neighboring elements. Therefore, only the diagonal blocks of global matrix need to be stored and calculated. Then, the problem of solving the huge global linear system is transformed into solving a series of local linear equations simultaneously. Finally, these small local linear equations would be solved by the LU decomposition method in parallel on GPU platforms. Two typical cases, including subsonic flows over a bump and a NACA0012 airfoil, were simulated and compared with the multi-grid explicit Runge-Kutta scheme. The numerical results demonstrated that the present implicit method can reduce the iterations significantly. Meanwhile, the implicit solver has shown at least 10x speedup over the multi-grid Runge-Kutta scheme in all cases.
2021, 53(6): 1586-1598.
doi: 10.6052/0459-1879-20-404
The metal droplet deposition manufacturing technology adopts a point-by-point stacking method, which provide an unsupported manufacturing method for oblique column deposition with high flexibility. In this paper, a lattice Boltzmann model is established for simulating the continuous deposition process of the oblique column, and the horizontal displacement of the droplet on the solidification surface is studied. According to the charging and discharging process of surface energy, the deposition process is divided into four stages: falling, rapid expansion, slow expansion, and rebound. The forces on the deposited droplet are analyzed by the trend of surface energy, the gravitational potential energy, the kinetic energy, and the viscous dissipation. The internal flow of droplet is sliding in the expansion stage and rolling in the rebound stage. The internal flow of the droplet shows sliding state in the expansion stage and rolling state in the rebound stage. The acceleration of the deviation mainly occurs in the expansion stage, while the deviation distance occurs in the rebound stage. Combined with the forces in the expansion stage, it is concluded that the main driving forces of displacement are gravity and capillary force. With the increase of the droplet axial distance, the acceleration in expansion stage is shortened, and the peak of velocity is increased, so that the horizontal deviation is first increased and then decreased. This staged feature stems from the competitive relationship between the acceleration period and the maximum speed in the deviate motion. Under different deposition heights and solid-liquid wettability, the deviation distance maintains the same trend. Under a certain axial distance, the deviate distance decreases with the increasing solid-liquid wettability, or the increasing deposition height. The evolution tendency of the horizontal deviation distance is fitted, and the scanning step is optimized to realize the uniform deposition of the inclined column whose inclination angle is consistent with the theoretical result.
2021, 53(6): 1599-1608.
doi: 10.6052/0459-1879-21-022
The controllable interface adhesion of attachment and detachment has important application requirements in climbing devices, adhesion switches and mechanical grippers. In present paper, the influence mechanism of external magnetic field and film's initial curvature on the interfacial adhesion of a magnetic sensitive film/substrate is studied. The peel-test of the magnetic sensitive thin film with initial curvature on a substrate as well as the corresponding theoretical study are respectively carried out. Both the experimental and theoretical results indicate that the interfacial adhesion force of the magnetic sensitive thin film/substrate increases with increasing the initial curvature of the film, and the external magnetic field can enhance the interfacial adhesion force. Compared with the steady-state peel-off force of a flat thin film that is independent on the bending stiffness, the bending stiffness would decrease the steady-state peel-off force of the film with initial curvature. The interface effective adhesion energy is further considered from the energy point of view, which can disclose the comparing mechanisms of the film's bending energy, the potential energy of external magnetic field and the adhesion energy. Lastly, based on the experimental and theoretical results, a simply mechanical gripper controlled by both the magnetic field and film's initial curvature is proposed, which can continuously realize the gripping, transport and release of an object. The results obtained in the present paper can not only be helpful for understanding the interface reversible adhesion mechanism actuated by multi-field, but also provide a novel approach to design functional devices with controllable interface adhesion.
2021, 53(6): 1609-1621.
doi: 10.6052/0459-1879-21-091
In recent years, artificial neural networks (ANNs), especially deep neural networks (DNNs), have become a promising new approach in the field of numerical computation due to their high computational efficiency on heterogeneous platforms and their ability to fit high-dimensional complex systems. In the process of numerically solving the partial differential equations, the large-scale linear equations are usually the most time-consuming problems; therefore, utilizing the neural network methods to solve linear equations has become a promising new idea. However, the direct prediction of deep neural networks still has obvious shortcomings in numerical accuracy, which becomes one of the bottlenecks for its application in the field of numerical computation. To break this limitation, a solving algorithm combining Residual network architecture and correction iteration method is proposed in this paper. In this paper, a deep neural network-based method for solving linear equations is proposed to accelerate the solving process of partial differential equations on heterogeneous platforms. Specifically, Residual network resolves the problems of network degradation and gradient vanishing of deep network models, reducing the loss of the network to 1/5000 of the classical network model; the correction iteration method iteratively reduce the error of the prediction solution based on the same network model, and the residual of the prediction solution has been decreased to 10−5 times of that before the iteration. To verify the effectiveness and universality of the proposed method, we combined the method with the finite difference method to solve the heat conduction equation and the Burger’s equation. Numerical results demonstrate that the algorithm has more than 10 times the acceleration effect for equations of size larger than 1000, and the numerical error is lower than the discrete error of the second-order difference scheme.
2021, 53(7): 1912-1921.
doi: 10.6052/0459-1879-21-040
Since organisms can accomplish specific tasks through various motion forms, bionic design methods have been received extensive attention from scholars. Inspired by the fact that earthworms have excellent mobility and adaptability in a variety of environments, earthworm-like robots have been proposed and applied in search and rescue, medical treatment and other fields. However, existing earthworm-like robots generally realize rectilinear motion through axial deformation of its body segments, which cannot be applied to realize the erecting function of snake organisms. In order to solve the problem that existing earthworm-like robot cannot erect, a bio-inspired flexible joint with nonlinear multi-stable property is proposed. Based on the proposed bio-inspired flexible joint, a multi-segment bio-inspired erecting structure is built to realize the erecting function of inchworms, snakes and other organisms. First, the model of the bio-inspired erecting joint is proposed. The potential energy of multi-segment bio-inspired erecting structure is obtained, and the dynamic model of the multi-segment bio-inspired erecting structure is established. Then, based on the potential energy and extremum principle, the structural design criteria is proposed to realize required erecting configuration. The effectiveness of structural design criteria is verified and the condition to trigger required configuration is studied by using the dynamic model. Finally, according to different design requirement for the number of erecting segments, corresponding bio-inspired erecting structure is designed. The results show that the design criteria of structural parameters can make the multi-segment bio-inspired erecting structure reach the required erecting configuration and maintain stable at the required erecting configuration. Besides, based on the basin of attraction of different stable configurations, the configuration triggering criteria of the bio-inspired erecting structure is studied, and the configuration triggering criteria composed of the excitation variables and configuration variables is revealed, which provide a theoretical basis for configuration switching of the bio-inspired erecting structure. The bio-inspired erecting structure proposed in this paper provide guidelines for function expansion of the earthworm-like robot. It is also a further improvement of the bionic design theory.
2021, 53(7): 2023-2036.
doi: 10.6052/0459-1879-21-176
Phase equilibrium calculations of complex fluids in shale gas reservoirs require the establishment of advanced numerical models that consider capillary effects, and the design of fast and reliable algorithms to handle the various components in the reservoir fluids in practical working conditions. In this study, we develop a thermodynamically consistent VT-type pore-scale flash calculation scheme based on realistic equations of state suitable for oil/gas reservoirs, e.g. the Peng-Robinson equation of state. The effect of capillarity has been incorporated in the scheme for a more accurate description of the thermodynamic properties of shale gas, and the diffuse interface model is applied to establish a dynamic evolution scheme in the phase equilibrium process, and a convex splitting method is used to model the evolution of compositional moles and volume. In order to accelerate the iterative flash calculations for realistic reservoir fluids containing a large number of components, a self-adaptive deep learning algorithm is developed in this paper with a novel structure to achieve wider applicability to various components in different fluids. The input and output features of the neural network are selected as the key thermodynamic features on the basis of thermodynamic analysis, and the network hyper-parameters have been carefully tuned to achieve a better performance on both accuracy and efficiency. Advanced deep learning technics resolving overfitting problems have been applied in our algorithm. The trained model significantly accelerates the conventional flash calculation based on iterative methods, while a good prediction accuracy has been preserved. Phase stability test and phase splitting calculations are automatically incorporated in our prediction, and we can significantly capture the effect of capillarity on phase equilibrium behaviors. Such a fast, accurate and reliable shale gas phase equilibrium calculation scheme using deep learning algorithms can provide an initial phase distribution field with physical meanings for subsequent multiphase flow simulations, while the number of phases can be also determined. The thermodynamic information and analysis can also be used as a thermodynamic basis for a multiphase numerical model with built-in physical conservation.
2021, 53(8): 1-12.
doi: 10.6052/0459-1879-21-229
The shock tunnel ground test is vitally important to the research of the high-enthalpy aerodynamic characteristics of hypersonic vehicles, and the high-precision aerodynamic measurement is the key technology. When a force measurement test is conducted in an impulse shock tunnel, the flow field is established instantly after the starting process of shock tunnel, at this time, the great impact loads are acting on the force measurement system. The force measurement system is excited under the action of instantaneous impact, and the inertial vibration signal of the system cannot be rapidly attenuated during the short test time. The output signal of the balance will contain the interference due to the inertial vibration, which leads to a bottleneck in the further improvement of the accuracy of the transient force test. In order to improve the force measurement accuracy in the short-duration shock tunnel, the development of high-precision dynamic calibration technology is the key method to improve the performance of balance affected by inertial interference. Therefore, in this paper, Recurrent Neural Network is used to train and intelligently process the balance dynamic calibration data, aiming to eliminate the vibration interference signals in the output dynamic signals. The error analysis of the current method is carried out, and the reliability of the current method is verified. The method is applied to the data processing of force test obtained in shock tunnel, and the effect of inertial vibration on the output signal of the balance is effectively reduced. According to the sample verification analysis of the intelligent model, the relative error of each component load is relatively small, where the case of high-frequency axial force component is about 1%. In the verification of wind tunnel force test data, the good results are also obtained, which are compared with those processed by the Convolutional Neural Network model.
2021, 53(8): 1-9.
doi: 10.6052/0459-1879-21-168
Phononic crystals represent a special kind of artificial periodic composite materials. The peculiar band-gap characteristics provide potential applications in the vibration reduction, wave filtering, sound insulation and acoustic functional devices. However, how to accurately manipulate acoustic and elastic waves is a major challenge for designing phononic crystals. The conventional design method is based on matching the specific application requirements by analyzing and adjusting the geometrical and material parameters of the phononic crystal structures. This method has a low efficiency and can hardly achieve the optimal performance. An artificial neural networks inverse design method for muti-layered phononic crystals based on the Softmax logistic regression and the multi-task learing is proposed in this study. In the proposed method, the Softmax logistic regression is used to choose the material type and the multi-task learing is used to determine the material distribution for each area of the multi-layered structure, so the phononic crystal reverse design problem is transformed into the classification problem of multi-component materials for the unit cell by the proposed method. First, a large number of the samples for the topological structures are randomly generated. Second, the band-gap structures of the samples are obtained by parallel finite element calculation. After that, the relationship between the topological structures and the band-gaps are established by the neural networks. Finally, the trained neural network is ultimately employed to design a phononic crystal structure with the targeted band-gaps, that is, the targeted band gap is used as the input of the neural network, and the trained neural network will output the corresponding cell topology of the phononic crystal unit cell directly. The example shows that the proposed method can obtain one-dimensional (1D) phononic crystals with the targeted band-gaps for the specified application requirements quickly and efficiently. This method provides a new way for the inverse design of phononic crystals.
2021, 53(7): 1807-1813.
doi: 10.6052/0459-1879-21-142
The flow field behind a rotating cylinder with Reynolds number Re = 20000 ~ 90000 and relative speed ɑ = 0 ~ 0.72 was measured experimentally, and the velocity distribution and turbulence distribution at different sections behind the rotating cylinder were analyzed. The flow around a rotating cylinder is numerically simulated by LES method, and the characteristics of the flow field around a rotating cylinder are analyzed. Finally, the theoretical model is used to analyze the flow field variation and came to the following conclusions: When the cylinder rotates counterclockwise, with the increase of the relative speed at the same Reynolds number, the position of the velocity mutation below the wake region of the rotating cylinder moves up with the increase of the relative speed, while the position of the velocity mutation above remains unchanged. With the increase of Reynolds number, the position of velocity mutation below the wake region of the rotating cylinder moves down to a small extent. Through numerical simulation, it is found that the position of the lower vortex behind the cylinder moves up obviously after the cylinder rotates, and the amplitude is large. The lower free shear layer has obvious upward movement, while the upper free shear layer has little change in position. Finally, through theoretical analysis, it is found that the upward movement of the lower vortex on the rear side of the rotating cylinder has a significant effect on the lift force of the rotating cylinder. Under the condition of high Reynolds number and low relative speed, the change of the lower vortex position on the rear side of the rotating cylinder has an important effect on the lift force of the rotating cylinder and the change of the free shear layer in the wake region.
2021, 53(7): 1973-1984.
doi: 10.6052/0459-1879-21-153
Time-dependent transient heat conduction problems are widely encountered in aerospace, civil engineering, metallurgical engineering, etc., and for such problems, accurate and fast numerical approaches have always attracted attention in the past decades. To achieve this goal, this paper proposes an unconditionally stable single-step time integration method for general transient heat conduction systems. In the proposed method, the temperature vector and its time derivative are formulated independently by the Langrage interpolation function, and then the relation between the temperature vector and its time derivative is defined with the weighted residual method. Theoretical analysis, including convergence rate and amplification factor, illustrates that the proposed method is strictly second-order accurate for the temperature vector and its time derivative, and it has the strong algorithmic dissipation (L-dissipation), meaning that it can quickly filter out the unwanted numerical oscillations in the high-frequency range. At present, most existing time integration methods, such as the Crank-Nicolson method and the Galerkin method, are unconditionally stable for linear transient heat conduction systems, but they are conditionally stable for nonlinear ones. To this end, this work improved the stability analysis theory for nonlinear transient heat conduction systems proposed by Hughes and used the improved stability analysis theory to design the free parameters of the proposed method. Because of this reason, the proposed method is unconditionally stable for both linear and nonlinear transient heat conduction problems. Due to the desirable algorithmic stability, the proposed method can still provide accurate and stable predictions for nonlinear transient heat conduction problems where the excellent Crank-Nicolson method fails. Some linear and nonlinear transient heat conduction problems are solved in this paper, and the results of these problems show that compared to the currently popular time integration methods, such as the Crank-Nicolson method and the backward difference formula, the proposed method enjoys noticeable advantages in accuracy, dissipation and stability.
2021, 53(7): 1859-1869.
doi: 10.6052/0459-1879-21-140
As an important component transporting resources such as oil and mineral ores mixture from the seabed to the surface in ocean engineering, vortex-induced vibration (VIV) of flexible risers can be encountered when the risers are subjected to the external environmental conditions. As VIV can lead to structural fatigue for the riser system, which threatens to the facility safety during deepsea resource exploitation, it is of great significance to investigate VIV mechanism and dynamics. Therefore, VIV dynamics of a flexible fluid-conveying riser undergoing external shear current is studied based on the combination of the Euler-Bernoulli beam theory and the semi-empirical hydrodynamic model. The finite element method and Newmark-β method are adopted to discretize and solve the governing equation. The model is firstly validated by comparing with the experimental data in order to examine the accuracy of the present model. Subsequently, cross-flow (CF) VIV response of the fluid-conveying riser is mainly examined and analyzed while various internal flow velocity and fluid density are considered and changed. The results show that when the flexible riser is subjected to both internal flow and shear current, there appears multi-frequency response for CF VIV. And the CF vibrating frequency and the CF root mean square (RMS) displacement are evidently influenced by the internal flow velocity and fluid density. With the increase of the internal flow velocity and fluid density, the CF vibrating frequency decreases while the RMS displacement shows an increasing trend in CF direction. Furthermore, in addition to the variation of the CF vibrating frequency and RMS displacement, the change of internal flow densities can cause notable mode and frequency transitions.
2021, 53(7): 1814-1822.
doi: 10.6052/0459-1879-21-171
High speed and shock compression behind the bow shock of an aircraft head result in very high temperature, which would subsequently lead to a conductivity plasma flowfield around the vehicle. The plasma gas provides a direct working environment for the application of magnetic field. The magnetohydrodynamic (MHD) flow control, which uses the magnetic field to alter the trajectory of ions or electrons, can improve the aerodynamic characteristics of hypersonic vehicles effectively. It has potential prospects on aerodynamic force control and aerodynamic heating management. Besides, the development of superconducting materials and electromagnetic technology contribute to a great upsurge of MHD flow control research significantly. Although research work has been carried out in the field of MHD flow control at home and abroad, its experimental investigation is still challenging. And for the measurement of pressure and heat flux, there is no systematic conclusion because of the limited test conditions and measurement techniques. The results of different researchers may be different from each other and from the theoretical results and numerical simulations. Thus, the influence on the shock stand-off distance, pressure and heat flux under MHD flow control deserves an in-depth investigation. Besides, the numerical simulations and theoretical methods do also need reliable experimental data for variation. The aim of this review paper is to summarize and discuss the developments on MHD flow control technology based on high temperature real gas effect, including the experimental technique, numerical method, and the influence rules and dynamics mechanism of MHD flow control. Its development trend is also discussed and prospected in the paper.
2021, 53(6): 1515-1531.
doi: 10.6052/0459-1879-21-067
Graphene and other two-dimensional (2D) materials possess various excellent properties and hold great promises for next generation of electronic devices and other applications. The mechanical properties are of fundamental importance in the research and application of 2D materials. Despite the fact that 2D materials have been extensively investigated in the past two decades, efforts on the mechanical properties are strikingly lacking and vastly needed. Atomic force microscopy (AFM) is one of the most widely used tools for the mechanical characterizations of low-dimensional materials. Particularly, the AFM-based nano-indentation technique has been extensively employed to explore the mechanical properties of 2D materials. In this review, we first introduce the basic backgrounds of 2D materials and atomic force microscopy. The mechanism and theoretical background of AFM-based nano-indentation are then demonstrated. In the second part, we review the research work by employing nano-indentation on studying the in-plane mechanical properties of 2D materials. The measurement errors of AFM-based nano-indentation and their origins are also discussed. Nano-indentation is perfectly suitable for the in-plane/intralayer mechanical measurement but also greatly limited in probing the out-of-plane/interlayer elasticity, due to the extreme anisotropy of 2D materials. Therefore, in the third part, we introduce an unconventional AFM-based technique - Angstrom-indentation which allows for sub-nm deformation on 2D materials. With such a shallow indentation depth comparable to the interlayer spacing of 2D materials, Angstrom-indentation is capable of measuring and tuning the interlayer van der Waals interactions in 2D materials. The interlayer elasticities of graphene and graphene oxide measured by Angstrom-indentation are discussed as examples in the third part. In the final part, we give a quick overview of a new type of 2D material - van der Waals heterostructure and its novel mechanical properties. We also discuss the potential application of Å-indentation in the investigation of the mechanical properties of van der Waals heterostructures.
2021, 53(4): 929-943.
doi: 10.6052/0459-1879-20-354
This paper experimentally and numerically investigates the fluid-structure interaction between a spark-induced bubble and a floating structure. The boundary integral method is adopted to simulate the bubble dynamic behaviors and the auxiliary function method is used to improve the computational accuracy of the nonlinear fluid-structure interaction. The double-node method is employed to maintain the computational stability of the gas-liquid-solid interaction line. Besides, we use the underwater electric discharge technique to generate bubbles and the high-speed photography to record the bubble dynamics and the structural responses. Firstly, we compare the numerical result with the experimental data and favorable agreement is achieved which validates this numerical model. Through parametric study with respect to the dimensionless distance $\gamma _{s} $ from the initial bubble center to the floating structure (the reference length is the maximum bubble radius), we then find that (1) as $\gamma_{s} $ increases from 0.2 to 2, five types of jetting pattern such as necking together with annular jet ($0.2\leqslant \gamma_{s} \leqslant 0.3)$, contacting jet ($0.4\leqslant \gamma_{s} \leqslant 0.6)$, non-contacting jet ($0.7\leqslant \gamma_{s} \leqslant 1)$, collision of a jet directed towards the floating body and a counter-jet ($1.1\leqslant \gamma_{s} \leqslant 1.3)$ and individual counter-jet ($1.4\leqslant \gamma_{s} \leqslant 2)$ can be formed; (2) it is also found that the velocity of the jet directed towards the structure first increases, then decreases and finally increases again as $\gamma_{s} $ increases; additionally, it may be in the order of $\sim$1000m/s when $\gamma _{s} $ varies from 0.7 to 0.9; as $\gamma_{s} $ increases, the counter-jet velocity increases; (3) under the conditions of the presented experiments, the bubble migrates towards the floating structure when $\gamma_{s} <\mbox{1.5}$ due to the stronger Bjerknes attraction of the floating structure than the Bjerknes repellence of the free surface on the bubble during the collapsing phase. When $\gamma_{s} \geqslant \mbox{1.5}$, however, the free surface has stronger effects on the migratory behavior of the bubble than the floating structure which causes the bubble to migrate away from the free surface at the collapse stage.
2021, 53(4): 944-961.
doi: 10.6052/0459-1879-20-357
Bubble directional transportation using the superhydrophobic surfaces of different specific geometry in the water has broad application prospects in the fields of mineral flotation and biological incubation. The surface orientation of the planar straight superhydrophobic surfaces is a crucial parameter for the related engineering structures. However, it is still unclear that the effect of surface orientation on the bubble slipping along the inclined surface. The high-speed shadowgraphy is used to study the movement characteristics of the slipping bubble ($D_{eq}=2.4$ mm, $Re=500$ $\sim$ 700, $We=7$ $\sim$ 13) on the superhydrophobic linear trajectory with the width of 2 mm under different surface orientations ($-90^\circ\leqslant \beta \leqslant 90^\circ$) and inclination angles ($45^\circ\leqslant \alpha \leqslant 75^\circ$). The slipping velocity of the bubble ($u)$ on the trajectory is approximately stable, and the shape like semi-bullet with multi-ridges. The slipping bubble can be divided into two shape types: the stable and the unstable according to the fluctuation level of the gas-liquid interface. Stable bubble only appear when the inclination angle is small and the azimuth angle is large ($45^\circ\leqslant \alpha <70^\circ$, $| \beta | \geqslant 45^\circ$). As $\alpha $ changes, two kinds of $u$-$\beta $ relations can be found: When $\alpha \leqslant 65^\circ$, the slipping velocity is approximately a unimodal distribution about $\beta =0^\circ$ (the maximum sliding velocity at $\beta =0^\circ$); When $\alpha \geqslant 70^\circ$, the azimuth angle has no significant influence on $u$. The maximum sliding velocity can be upto 0.66 m/s ($\beta =0^\circ$, $\alpha =70^\circ$), which is much higher than that of the free-rising bubble of the similar size ($\sim$0.25 m/s), mainly as a combined effect of the wall-wettability and the inertial force. Surface orientation ($\beta$) and trajectory inclination angle ($\alpha$) affect the slipping velocity and the stability of the gas-liquid interface by changing the driving force, as a buoyance component, of the bubble along the trajectory direction and the bubble frontal area.
2021, 53(4): 962-972.
doi: 10.6052/0459-1879-20-405
Water-air two-phase flow can be found in many practical engineering projects in various fields. To simulate water-air two-phase flow with high accuracy has always been a challenging problem and a highlight in the realm of computational fluid dynamics. Based on the assumption that both water and air can be considered as incompressible fluid, for free surface flow in open water areas, the WENO-THINC/WLIC model for water-air two-phase flow is therefore established. In the developed model, the fifth-order accurate weighted essentially non-oscillation (WENO) scheme is used to solve the Navier-Stokes equation for fluid flows, and the improved multi-dimensional tangent of hyperbola for interface capturing scheme with weighted line interface calculation method (THINC/WLIC) is adopted to track the interface. The fractional step method is applied to discretize and solve the governing equations, the pressure projection method is adopted to compute the pressure field, and the third-order accurate total variation diminishing (TVD) Runge-Kutta (RK) method is used to discretize the temporal terms. In order to verify the model, it is applied to simulate two benchmarks of interface evolution subjected to an external velocity field, Zalesak's disk and shearing vortex, the linear sloshing, and the dam-breaking flow problem. Through comparison of the simulated results with the analytical or experimental ones, adaptability and accuracy of the water-air two-phase model are discussed. The analysis indicates that the simulation outputs are in good accordance with theoretical or experimental results, which means the model is capable to simulate incompressible water-air two-phase flows. With the further improved WENO schemes and THINC schemes, more precise prediction results for water-air two phase flow problems can be achieved with the proposed combined WENO-THINC model.
2021, 53(4): 973-985.
doi: 10.6052/0459-1879-20-430
The characteristics of shale gas reservoir are expressed in terms of complex pore structure and multiple gas occurrence pattern. The influence of organic pore shape on confined gas adsorption and flow behavior is not clear, which causes the inaccuracy to understand gas transport mechanisms in shale gas reservoir. To solve this problem, Grand canonical Monte Carlo method is first applied to simulate gas adsorption process in different shapes of organic pore (circular pore, slit pore, triangle pore, square pore). We found that gas adsorption behavior in different shapes of pores conforms well with the Langmuir adsorption pattern. The absolute adsorption, excess adsorption and gas adsorption parameter change with pore size and pore pressure is analyzed and the influence of pore shape on gas adsorption is studied. The mathematical model of adsorbed gas surface diffusion and free gas slip flow in different shapes of organic pore is established based on the understanding of gas adsorption pattern in different shapes of organic pore. The respective contribution of adsorbed gas flow and free gas flow on total gas permeability is studied in organic pores with different pore shape and pore size combining molecular simulation results. The results indicate that the slit pore exhibits the largest value of maximum gas concentration, Langmuir pressure and the weakest adsorbed gas
, Available online
The study of wave propagation in granular materials is of great significance in metamaterial manufacturing. The boundary design of wave-conducting metamaterials needs to consider the reflection and absorption of stress waves. First, the wave propagation behavior in a one-dimensional particle chain has been studied. According to the difference in the maximum kinetic energy that the particles can obtain at different positions from the boundary, the definition of the boundary area is given. Then the stress wave propagation behaviors of multiple sets of two-dimensional particle samples under impact load are analyzed. The influences of different boundary shapes and particle arrangement on the propagation behavior of stress waves in the pro-border zone have been considered. The results show that the arrangement of particles in the pro-border zone mainly affects the relative position and local porosity of particles near the boundary. The stress wave reflected by the boundary propagates directly in the pro-border zone in the shape of the boundary line. The more complicated the boundary situation (high local porosity, random arrangement of particles), the more accurate the conclusion. The wave velocity mainly determines the shape of the wave-front outside the pro-border zone i.e. in the material center area. The convergence effect of the arc boundary on the wave reflection and the dispersion effect caused by the arrangement of the particles in the pro-border zone are two competing factors, which together determine the reflection process of the wave in the pro-border zone. Finally, the changes of the force chain network in the pro-border zone before and after reflection are analyzed. The distribution of kinetic energy intuitively reflects the phenomenon of reflection hysteresis. The process of particle contact and rebound in the boundary area corresponds to the storage and release of energy. This research will provide reference for the handling of boundary problems in metamaterial design.
, Available online ,
doi: 10.6052/0459-1879-21-242
The powder spreading process is one of the key processes in the powder-bed-based additive manufacturing (AM) technology. The roller-spreading parameters include the powder spreading layer thickness H, roller’s diameter D, roller’s rotational speed ω and translational velocity V, which have a major impact on the powder spreadability in AM processes. In this paper, the nylon powder was taken as the research object, and the discrete element method (DEM) was deployed to simulate the nylon powder spreading process by a roller. The three powder spreadability indicators including the deposition fraction, percent coverage and deposition rate were established. The central composite design (CCD) model was used to generate 30 groups of simulation cases. The regression models of three powder spreadability indicators were fitted by the response surface method (RSM). The analysis of variance was used to prove the accuracy and predicting effectiveness of regression models. In addition, the effect of process parameters on powder spreadability indicators was analyzed in detail. The results showed that the powder spreading layer thickness H was a leading influencing factor. The roller’s translational velocity V was a less important influencing factor. The roller’s diameter D and rotational speed ω had a slight influence on powder spreadability indicators. Both the H and D with V were determined as the main interactive factors on powder spreadability indicators. The three powder spreadability indicators were taken as the optimization goal, and the multi-objective optimization of roller-spreading parameters was carried out by the expectation method. The predicted optimal combination of powder spreading parameters and powder spreadability indicators were obtained. Moreover, the optimal results were verified through the experiments. The results showed that the predicted results of powder spreadability indicators were in good agreement with experimental results. The research results in this paper can provide guidance for the optimization of roller-spreading parameters in AM.
, Available online ,
doi: 10.6052/0459-1879-21-240
Tight oil reservoirs have achieved certain oil increase effect by supplementing formation energy with water-injection huff and puff. However, formation pressure and production decrease rapidly after multiple rounds of water injection. In order to improve the oil enhancement effect of tight oil reservoirs, changing the development method quickly became hotspot research. This paper analysis the stress field distribution near the tip of type I fracture considered the complex fracture morphology of tight oil reservoirs based on Irwin theory and elastic mechanics. A multi-fracture cross-fracture propagation model is established based on seepage mechanics, fractured tight reservoir characteristics and dynamic fracture seepage characteristics. The fracture propagation length is obtained based on the fracture propagation mechanism and the energy conservation principle. It is proposed to turn water-injection huff and puff into unstable pulse water injection according to the principle of reverse imbibition in tight oil reservoirs. Comparative analysis of two energy supplementary generation methods, water-injection huff and puff and pulse water injection, predicting cumulative oil production, pressure and remaining oil distribution in 10 years. The results show that the net internal pressure of the fracture increases with the increase of water injection, and the stress field intensity factor also increases. When the stress field intensity factor reaches the fracture toughness, it will expand at the fracture tip. The expanded and extended natural fractures communicate with each other, presenting irregular and complex fracture networks. Reverse imbibition mainly occurs in the complex fracture networks. Pulse water injection has a high cumulative oil production, a wide area of water injection and strong reverse imbibition. The findings of this study can help for better understanding of the transformation of water-injection huff and puff into pulsed water injection from horizontal wells in fractured tight oil reservoirs. It can give full play to the effects of reverse imbibition and linear displacement. This research provides guidance for it can achieve the purpose of effective oil displacement of the dynamic fracture network.
, Available online
The fractional-order Bingham model of magnetorheological fluid damper has simple structure and can better describe the hysteretic characteristics of the system. The vibration control of a nonlinear vehicle suspension system with magnetorheological fluid damper under harmonic excitation is studied, where the single-degree-of-freedom 1/4 vehicle suspension system with fractional-order Bingham model of magnetorheological fluid damper is considered. The primary resonance response of suspension system with fractional-order Bingham model under sky-hook damping semi-active control is analyzed, and the approximate analytical solution is obtained by means of averaging method. The amplitude-frequency response equation of the steady-state solution of the suspension system is obtained, and the stability condition of the suspension system is also obtained according to Lyapunov's stability theory. By comparing the amplitude-frequency response curves of the numerical solution and approximate analytical solution, the accuracy of the approximate analytical solution has been verified. The influence of semi-active control on the ride comfort of the vehicle is illustrated by the root mean square values of acceleration of the sprung mass in the vertical direction, it is found that the semi-active control strategy of sky-hook damping can not improve the ride comfort of vehicle in low frequency excitation region of road. Therefore, a combined control strategy of passive control and semi-active control is proposed, and the influence of semi-active control parameter on the vibration control effect is analyzed. The results show that the combined control strategy can not only improve the ride comfort of the vehicle, but also effectively suppress the primary resonance vibration amplitude of suspension system.
, Available online ,
doi: 10.6052/0459-1879-21-137
The rolling resistance between particles plays an important role in the stability of the particulate systems. In a conventional discrete element method, the rolling resistance model between particles is usually made of springs, dashpots, and sliders in the rotational direction. The particles rolling kinetic energy is dissipated by the viscous (moment) and friction forces. With this model, the viscous force (moment) is directly related to the rolling velocity. Consequently, the dynamic dissipation capacity of particles close to the static state becomes weaker with the rolling velocity decreasing. It is known that the time required to simulate a particle rolling with a velocity close to zero by using the traditional discrete element method is longer than the experimental results. To solve this problem, the mechanism of rolling resistance caused by material hysteresis is analyzed based on tribological principle, and a new discrete element model of hysteresis rolling resistance (HDEM) is established. A hysteresis spring with velocity-independent kinetic energy dissipation is proposed, and its constitutive law’s formula is derived. To verify the new rolling resistance model, the free-rolling of a single round particle specimen on a flat surface is measured through a physical experiment. The measured data are compared with the results simulated by the new rolling resistance model HDEM and the conventional rolling resistance model. The results show that the results based on HDEM are more consistent with the experimental data, and the particle oscillation frequency is in better agreement with the experimental phenomenon observed.
, Available online
Constitutive relations of granular materials are of great significance to many fields, such as geotechnical engineering. Different from traditional phenomenological constitutive theory, this study explores a micromechanics-informed data-driven constitutive modelling approach for granular materials via machine learning models. On the basis of Vogit’s homogenization assumption, an analytical small-strain stress-strain relation is established. This relation uniquely determines a group of micromechanical fabric variables associated with the constitutive behavior of granular materials. These recognized variables, together with principal strain and stress sequence pairs reflecting macroscopic properties of granular materials, are obtained via a series of discrete element models of triaxial compression tests. Considering the fact that these microscopic fabric tensors are internal variables, which cannot be directly used as inputs of a material constitutive model, a directed graph is introduced to incorporate microstructural information implicitly in the prediction of stress-strain responses. The gated recurrent unit (GRU) based recurrent neural networks are used as basic deep learning models to describe the mapping relation between nodes in the designed directed graph. In this study, the entire stress-strain prediction model can be assembled with two neural networks that are trained separately, after unfolding the directed graph from the target node to the source node. By testing the trained deep learning model based on brand new datasets, the results demonstrate that the proposed training approach can satisfactorily capture the multi-directional stress-strain responses with reversal loadings, such as conventional triaxial compression with unloading-reloading cycles, true-triaxial compression with constant intermediate principal stress (constant-b), and constant mean effective effective stress (constant-p) conditions with unloading-reloading cycles. The prediction results also show that the trained model possesses satisfactory interpolation and extrapolation capability. Considering the excellent ability of deep learning in terms of capturing the mechanical responses of granular materials and the unique features of open learning when new data is available, integrating a data-driven paradigm with theoretical constitutive models may be one of the important directions for constitutive research of granular materials.
, Available online ,
doi: 10.6052/0459-1879-21-221
The propeller wake dynamics is a fundamental but very complicated fluid mechanics problem. Its complexity comes from its sophisticated vortex system, which keeps evolving in high-speed shear layer flow. The mechanism of propeller wake behaviors such as the evolution from stable regime to unstable regime and the flow phenomenon in a complex operating environment have always been difficult and hot topics in the field of fluid mechanics. From the perspective of engineering applications, propeller wakes are directly related to the macroscopic characteristics of marine structures, a better understanding of the dynamic characteristic of the propeller wake under multiple operating conditions helps to improve the propulsion performance related to vibration, noise, and structure problems and has important practical significance for the design and optimization of next-generation propellers with good comprehensive performance. In this paper, the propeller wake dynamics are analyzed numerically using DDES, LES and NTM methods and experimentally based on PIV flow measurements, and the triggering mechanism of the instability of the propeller wake is revealed. Based on the evolution mechanism of the tip vortex in the uniform inflow, an evolution model of the tip vortices is proposed. The proposed model can accurately reproduce the evolution process of propeller tip vortex, predict the instant and position of tip vortex merging, which is of great significance to the prediction and control of propeller flow noise and the design of propellers with excellent performance.
, Available online ,
doi: 10.6052/0459-1879-21-151
2016, 48(4): 756-766.
doi: 10.6052/0459-1879-16-159
摘要：
软体机器人是一类新型机器人，具有结构柔软度高，环境适应性好，亲和性强，功能多样等特点，有着十分广阔的研究和应用前景. 智能材料在软体机器人结构设计及实际应用中扮演了重要的角色，其特殊的驱动机制极大拓展了软体机器人的功能. 介绍了软体机器人的发展和研究现状，按其应用场合及功能总结了几种典型的软体机器人. 从仿生机理的角度，介绍了蠕虫、弯曲爬行虫、鱼类游动等几类仿生运动机理以及其相应的软体机器人. 还按不同驱动类型将软体机器人归纳为气动、形状记忆合金、离子交换聚合物金属复合材料、介电高弹体、响应水凝胶、化学燃烧驱动等类型. 介绍了软体机器人的制作方法与工艺，分析了目前软体机器人研究的主要挑战，提出对未来研究的展望.
软体机器人是一类新型机器人，具有结构柔软度高，环境适应性好，亲和性强，功能多样等特点，有着十分广阔的研究和应用前景. 智能材料在软体机器人结构设计及实际应用中扮演了重要的角色，其特殊的驱动机制极大拓展了软体机器人的功能. 介绍了软体机器人的发展和研究现状，按其应用场合及功能总结了几种典型的软体机器人. 从仿生机理的角度，介绍了蠕虫、弯曲爬行虫、鱼类游动等几类仿生运动机理以及其相应的软体机器人. 还按不同驱动类型将软体机器人归纳为气动、形状记忆合金、离子交换聚合物金属复合材料、介电高弹体、响应水凝胶、化学燃烧驱动等类型. 介绍了软体机器人的制作方法与工艺，分析了目前软体机器人研究的主要挑战，提出对未来研究的展望.
2017, 49(1): 3-21.
doi: 10.6052/0459-1879-16-348
摘要：
作为隧道及地下工程学科的3个基本问题，隧道围岩稳定性、支护——围岩相互作用和结构体系的动力响应一直都是本学科研究的核心问题，本文围绕上述问题重点分析了隧道围岩力学特性及其载荷效应，建立了深浅层围岩结构力学模型，并通过分析深层围岩中结构层稳定性得到了围岩特性曲线的解析公式，提出了围岩结构性特点及载荷效应的计算方法；通过对隧道支护与围岩作用关系的分析，将支护与围岩的动态作用分为4个阶段：即自由变形、超前支护、初期支护和二次衬砌阶段.由此提出了动态作用全过程的描述方法；基于广义与狭义载荷的理念，提出隧道支护具有调动和协助围岩承载基本功能的观点，明确了两种功能的实现方式，即通过围岩加固、超前加固及锚杆支护实现调动围岩承载，通过支护结构协助围岩承载；针对复杂的隧道支护结构体系，提出了多目标、分阶段协同作用动态优化概念，可使各种支护结构的施作实现时间和空间上的协调，提高可靠性；针对极不稳定的复杂隧道围岩的安全性特点，建立了3种模式的安全事故机理模型，基于工程响应特点提出了安全性分级的新理念，并形成了分级指标体系和分级方法；针对水下隧道及富水围岩条件，建立了3种模式的隧道突涌水机理模型，提出了基于围岩变形控制的安全性控制理论和方法.最后，对本学科发展的热点和核心问题进行了分析和展望.
作为隧道及地下工程学科的3个基本问题，隧道围岩稳定性、支护——围岩相互作用和结构体系的动力响应一直都是本学科研究的核心问题，本文围绕上述问题重点分析了隧道围岩力学特性及其载荷效应，建立了深浅层围岩结构力学模型，并通过分析深层围岩中结构层稳定性得到了围岩特性曲线的解析公式，提出了围岩结构性特点及载荷效应的计算方法；通过对隧道支护与围岩作用关系的分析，将支护与围岩的动态作用分为4个阶段：即自由变形、超前支护、初期支护和二次衬砌阶段.由此提出了动态作用全过程的描述方法；基于广义与狭义载荷的理念，提出隧道支护具有调动和协助围岩承载基本功能的观点，明确了两种功能的实现方式，即通过围岩加固、超前加固及锚杆支护实现调动围岩承载，通过支护结构协助围岩承载；针对复杂的隧道支护结构体系，提出了多目标、分阶段协同作用动态优化概念，可使各种支护结构的施作实现时间和空间上的协调，提高可靠性；针对极不稳定的复杂隧道围岩的安全性特点，建立了3种模式的安全事故机理模型，基于工程响应特点提出了安全性分级的新理念，并形成了分级指标体系和分级方法；针对水下隧道及富水围岩条件，建立了3种模式的隧道突涌水机理模型，提出了基于围岩变形控制的安全性控制理论和方法.最后，对本学科发展的热点和核心问题进行了分析和展望.
2017, 49(1): 22-30.
doi: 10.6052/0459-1879-16-345
摘要：
岩溶隧道突水灾害具有“强突发、高水压、大流量、多类型”等显著特点，其灾变演化过程复杂、动力失稳规律尚不清楚.本文系统提出了不同类型突水灾害的发生条件、判据及安全厚度分析方法，剖析了近期研究进展及发展趋势.首先，给出了隧道突水灾害的概念、类型及构成三要素，从系统论角度分析了隧道突水的灾变过程；其次，总结了隧道突水灾害致灾机理、力学模型、失稳判据和最小安全厚度等方面的近期研究成果；最后，从构成三要素角度分析了隧道突水致灾机理方面的现状与问题，并提出了今后的发展趋势与方向，主要有：（1）灾害源固液气三相置换机制与释能模式，（2）突水通道多相物质迁移与流态演化规律，（3）隔水阻泥结构动力灾变演化机理，（4）突水通道破裂形成过程的模拟分析方法等.
岩溶隧道突水灾害具有“强突发、高水压、大流量、多类型”等显著特点，其灾变演化过程复杂、动力失稳规律尚不清楚.本文系统提出了不同类型突水灾害的发生条件、判据及安全厚度分析方法，剖析了近期研究进展及发展趋势.首先，给出了隧道突水灾害的概念、类型及构成三要素，从系统论角度分析了隧道突水的灾变过程；其次，总结了隧道突水灾害致灾机理、力学模型、失稳判据和最小安全厚度等方面的近期研究成果；最后，从构成三要素角度分析了隧道突水致灾机理方面的现状与问题，并提出了今后的发展趋势与方向，主要有：（1）灾害源固液气三相置换机制与释能模式，（2）突水通道多相物质迁移与流态演化规律，（3）隔水阻泥结构动力灾变演化机理，（4）突水通道破裂形成过程的模拟分析方法等.
2016, 48(4): 767-783.
doi: 10.6052/0459-1879-16-161
摘要：
视觉伺服控制是机器人系统重要的控制手段. 相比传统的在标定条件下使用的视觉伺服系统，无标定视觉伺服系统具有更高的灵活性与适应性，是机器人伺服控制系统未来重要的发展方向和研究热点. 本文从目标函数选择、控制器设计、运动轨迹规划三方面综述了无标定视觉伺服控制系统近年来的主要研究进展. 首先根据目标函数的形式，分析了基于位置的视觉伺服、基于图像的视觉伺服以及混合视觉伺服各自的特点与应用；在控制器设计方面，根据是否在设计过程中考虑机器人的非线性动力学特性，分别介绍了考虑机器人运动学与考虑机器人动力学的无标定视觉伺服控制器的设计，重点突出了雅克比矩阵的构造与估计方法；针对无标定视觉伺服系统运动轨迹可能存在的问题，从空间轨迹优化与障碍规避的角度，阐述了已有的可行解决方案. 最后，基于当前的研究进展展望了无标定视觉伺服的未来研究方向.
视觉伺服控制是机器人系统重要的控制手段. 相比传统的在标定条件下使用的视觉伺服系统，无标定视觉伺服系统具有更高的灵活性与适应性，是机器人伺服控制系统未来重要的发展方向和研究热点. 本文从目标函数选择、控制器设计、运动轨迹规划三方面综述了无标定视觉伺服控制系统近年来的主要研究进展. 首先根据目标函数的形式，分析了基于位置的视觉伺服、基于图像的视觉伺服以及混合视觉伺服各自的特点与应用；在控制器设计方面，根据是否在设计过程中考虑机器人的非线性动力学特性，分别介绍了考虑机器人运动学与考虑机器人动力学的无标定视觉伺服控制器的设计，重点突出了雅克比矩阵的构造与估计方法；针对无标定视觉伺服系统运动轨迹可能存在的问题，从空间轨迹优化与障碍规避的角度，阐述了已有的可行解决方案. 最后，基于当前的研究进展展望了无标定视觉伺服的未来研究方向.
2016, 48(4): 741-753.
doi: 10.6052/0459-1879-16-069
摘要：
从Inglis 和Griffith 的著名论文到Irwin 和Rice 等的奠基性贡献，对断裂力学中的线弹性断裂力学的K判据，界面断裂力学的G判据，和弹塑性断裂力学的J 判据作了扼要的综述. 介绍了在界面断裂力学G判据的基础上提出的界面断裂力学的K判据，以说明断裂力学的判据存在改进的可能性. 在综述中归纳出断裂力学判据中目前还没有较好解决的几个问题. 在总结以往断裂力学研究经验的基础上，指出裂纹端应力奇异性的源是对断裂力学判据存在的问题作进一步研究的切入点. 探讨了裂纹端应变间断的奇点是裂纹端应力奇异性的源的问题，从而对裂纹端应力强度因子的物理意义进行了讨论. 最后，阐述了进行可靠的裂纹端应力场的弹塑性分析是改进弹塑性断裂力学判据的关键，而进行可靠的裂纹端应力场的弹塑性分析的前提是要通过裂纹端应力奇异性的源的研究来获得作用在裂纹端的造成裂纹端应变间断的有限值应力.
从Inglis 和Griffith 的著名论文到Irwin 和Rice 等的奠基性贡献，对断裂力学中的线弹性断裂力学的K判据，界面断裂力学的G判据，和弹塑性断裂力学的J 判据作了扼要的综述. 介绍了在界面断裂力学G判据的基础上提出的界面断裂力学的K判据，以说明断裂力学的判据存在改进的可能性. 在综述中归纳出断裂力学判据中目前还没有较好解决的几个问题. 在总结以往断裂力学研究经验的基础上，指出裂纹端应力奇异性的源是对断裂力学判据存在的问题作进一步研究的切入点. 探讨了裂纹端应变间断的奇点是裂纹端应力奇异性的源的问题，从而对裂纹端应力强度因子的物理意义进行了讨论. 最后，阐述了进行可靠的裂纹端应力场的弹塑性分析是改进弹塑性断裂力学判据的关键，而进行可靠的裂纹端应力场的弹塑性分析的前提是要通过裂纹端应力奇异性的源的研究来获得作用在裂纹端的造成裂纹端应变间断的有限值应力.
2017, 49(3): 550-564.
doi: 10.6052/0459-1879-17-064
摘要：
工程中航空航天、船舶与海洋结构物及其上装备和精密仪器易受极端环境干扰和破坏，使得非线性隔振理论在近十年来迅猛发展；针对日益严峻的隔振和抗冲击等要求，工程师和科学家们已发展出各种不同的非线性隔振系统，包括主动、半主动、被动和复合隔振。利用非线性改善的被动隔振兼具传统被动隔振的鲁棒性和主动隔振的高效性成为振动控制领域的先进技术。本文主要综述了非线性隔振理论和应用的近十年进展，包括非线性隔振设计、建模、分析、仿真和实验。在隔振系统的构建中，既考虑了刚度非线性又考虑了阻尼非线性；动力学响应的研究中，既有确定性分析又有随机分析。首先提出了适用于非线性隔振系统改进的评价方式；其次综述了高静态低动态刚度隔振及其加强形式非线性阻尼加强和双层非线性隔振，混沌反控制技术、内共振影响、非线性能量阱应用等振动机制利用型隔振和非线性隔振功能材料。最后，对非线性隔振研究发展的热点和关键性问题进行了分析和展望。
工程中航空航天、船舶与海洋结构物及其上装备和精密仪器易受极端环境干扰和破坏，使得非线性隔振理论在近十年来迅猛发展；针对日益严峻的隔振和抗冲击等要求，工程师和科学家们已发展出各种不同的非线性隔振系统，包括主动、半主动、被动和复合隔振。利用非线性改善的被动隔振兼具传统被动隔振的鲁棒性和主动隔振的高效性成为振动控制领域的先进技术。本文主要综述了非线性隔振理论和应用的近十年进展，包括非线性隔振设计、建模、分析、仿真和实验。在隔振系统的构建中，既考虑了刚度非线性又考虑了阻尼非线性；动力学响应的研究中，既有确定性分析又有随机分析。首先提出了适用于非线性隔振系统改进的评价方式；其次综述了高静态低动态刚度隔振及其加强形式非线性阻尼加强和双层非线性隔振，混沌反控制技术、内共振影响、非线性能量阱应用等振动机制利用型隔振和非线性隔振功能材料。最后，对非线性隔振研究发展的热点和关键性问题进行了分析和展望。
2016, 48(3): 519-535.
doi: 10.6052/0459-1879-15-436
摘要：
斜拉桥的非线性动力学问题一直都是力学、结构和桥梁领域的研究热点.随着新材料(如碳纤维增强聚合物索)和新施工工艺的发展,斜拉桥的跨越能力不断得到提高,从而在桥梁建设中更具有竞争力.然而,斜拉桥跨度的增大和新材料的应用使结构变得更轻和更柔,使结构的非线性振动问题比以往更为突出,可能危及桥梁安全.基于课题组近年来对斜拉桥非线性动力学的研究,围绕大跨度斜拉桥的非线性建模理论及动力学问题,较为详细地评述近十年来国内外的研究进展情况.主要从斜拉索非线性动力学模型、梁的非线性动力学模型、索-梁组合结构的非线性动力学模型、斜拉桥整体非线性动力学模型与理论、以及斜拉桥的非线性振动实验等几个方面对斜拉桥非线性建模方法、力学模型、数学模型、求解方法及相应研究成果进行评述和讨论.研究结果表明,斜拉桥由于多柔性索和大跨度梁的耦合问题,以及环境载荷的复杂性,导致其具有丰富的非线性动力学行为.同时由于高维非线性系统求解方法的欠缺,整体斜拉桥非线性动力学行为又相当复杂,深入研究面临很大困难.最后,基于未来斜拉桥的发展趋势和可能面临的突出问题,对斜拉桥非线性振动问题今后的发展方向进行了探讨和展望.
斜拉桥的非线性动力学问题一直都是力学、结构和桥梁领域的研究热点.随着新材料(如碳纤维增强聚合物索)和新施工工艺的发展,斜拉桥的跨越能力不断得到提高,从而在桥梁建设中更具有竞争力.然而,斜拉桥跨度的增大和新材料的应用使结构变得更轻和更柔,使结构的非线性振动问题比以往更为突出,可能危及桥梁安全.基于课题组近年来对斜拉桥非线性动力学的研究,围绕大跨度斜拉桥的非线性建模理论及动力学问题,较为详细地评述近十年来国内外的研究进展情况.主要从斜拉索非线性动力学模型、梁的非线性动力学模型、索-梁组合结构的非线性动力学模型、斜拉桥整体非线性动力学模型与理论、以及斜拉桥的非线性振动实验等几个方面对斜拉桥非线性建模方法、力学模型、数学模型、求解方法及相应研究成果进行评述和讨论.研究结果表明,斜拉桥由于多柔性索和大跨度梁的耦合问题,以及环境载荷的复杂性,导致其具有丰富的非线性动力学行为.同时由于高维非线性系统求解方法的欠缺,整体斜拉桥非线性动力学行为又相当复杂,深入研究面临很大困难.最后,基于未来斜拉桥的发展趋势和可能面临的突出问题,对斜拉桥非线性振动问题今后的发展方向进行了探讨和展望.
2019, 51(1): 1-13.
doi: 10.6052/0459-1879-18-054
摘要：
随着航天重大工程的逐步实施,航天器正朝着超高速、超大尺度、多功能的方向发展,其面临的发射和运行环境也更加恶劣.航天器发射过程中的振动及其主/被动控制、在轨运行中大型柔性航天器动力学建模与动态响应分析、结构振动与飞行器姿态的混合控制等问题越来越复杂且难于处理;航天器结构的大型化和柔性化(如大阵面天线和太阳翼等)也对其地面试验和半实物仿真提出了挑战.本文着重介绍大型柔性航天器涉及到的动力学与振动控制问题,包括航天器发射过程中的整星隔振,大型柔性结构动力学建模与振动响应分析,大型柔性航天器的结构振动与姿轨控耦合动力学及其混合控制等.提炼出航天动力学与控制领域中亟待解决的若干基础科学问题,包括：多刚柔体系统动力学建模与模型降阶(涉及大变形柔性体动力学建模、多求解器合作仿真、模型降阶、组合结构动力学建模的解析方法等);复杂结构状态空间模型构建方法与能控性(涉及状态空间模型构建的理论与实验方法、复杂结构振动控制系统的能观性与能控性等);航天器姿态运动与大型柔性结构振动的混合控制律设计(涉及姿态机动与结构振动的鲁棒混合控制、执行机构与压电控制器的协同控制等).
随着航天重大工程的逐步实施,航天器正朝着超高速、超大尺度、多功能的方向发展,其面临的发射和运行环境也更加恶劣.航天器发射过程中的振动及其主/被动控制、在轨运行中大型柔性航天器动力学建模与动态响应分析、结构振动与飞行器姿态的混合控制等问题越来越复杂且难于处理;航天器结构的大型化和柔性化(如大阵面天线和太阳翼等)也对其地面试验和半实物仿真提出了挑战.本文着重介绍大型柔性航天器涉及到的动力学与振动控制问题,包括航天器发射过程中的整星隔振,大型柔性结构动力学建模与振动响应分析,大型柔性航天器的结构振动与姿轨控耦合动力学及其混合控制等.提炼出航天动力学与控制领域中亟待解决的若干基础科学问题,包括：多刚柔体系统动力学建模与模型降阶(涉及大变形柔性体动力学建模、多求解器合作仿真、模型降阶、组合结构动力学建模的解析方法等);复杂结构状态空间模型构建方法与能控性(涉及状态空间模型构建的理论与实验方法、复杂结构振动控制系统的能观性与能控性等);航天器姿态运动与大型柔性结构振动的混合控制律设计(涉及姿态机动与结构振动的鲁棒混合控制、执行机构与压电控制器的协同控制等).
2016, 48(5): 1126-1135.
doi: 10.6052/0459-1879-16-070
摘要：
黏弹性人工边界在场地地震反应和结构-地基动力相互作用等问题的计算中已得到了广泛的应用.地震波在黏弹性人工边界中的输入是通过将地震波转化为作用于人工边界处的等效载荷来实现的.计算等效节点载荷的常规方法默认边界节点对应区域内的应力为均布力，但实际上该节点对应区域内的应力分布通常是不均匀的.本文在有限元方法结合黏弹性局部人工边界的显式时域波动方法的基础上，建立了无限域散射问题地震波等效载荷计算的一种改进方法.该方法采用细化网格与应力积分相结合的方法计算人工边界等效节点力，有效地降低了人工边界上等效节点力的计算误差.以不同角度入射地震波的二维算例为例，算例给出的波场位移云图和节点位移时程曲线验证了本文方法的有效性，其计算精度与网格尺寸和地震波入射角度密切相关，且网格越小、入射角度越小，计算精度越高.对于相同的网格尺寸，本文采用方法的计算精度明显高于常规方法，尤其是对于斜入射问题优势更为明显.
黏弹性人工边界在场地地震反应和结构-地基动力相互作用等问题的计算中已得到了广泛的应用.地震波在黏弹性人工边界中的输入是通过将地震波转化为作用于人工边界处的等效载荷来实现的.计算等效节点载荷的常规方法默认边界节点对应区域内的应力为均布力，但实际上该节点对应区域内的应力分布通常是不均匀的.本文在有限元方法结合黏弹性局部人工边界的显式时域波动方法的基础上，建立了无限域散射问题地震波等效载荷计算的一种改进方法.该方法采用细化网格与应力积分相结合的方法计算人工边界等效节点力，有效地降低了人工边界上等效节点力的计算误差.以不同角度入射地震波的二维算例为例，算例给出的波场位移云图和节点位移时程曲线验证了本文方法的有效性，其计算精度与网格尺寸和地震波入射角度密切相关，且网格越小、入射角度越小，计算精度越高.对于相同的网格尺寸，本文采用方法的计算精度明显高于常规方法，尤其是对于斜入射问题优势更为明显.
2017, 49(3): 507-516.
doi: 10.6052/0459-1879-16-399
摘要：
页岩气是指赋存于富含有机质泥页岩中以吸附和游离状态为主要存在方式的天然气，中国资源量丰富，地域分布广泛。页岩气开采能缓解我国常规油气产量不足、煤化石燃料引起环境污染等问题，已成为中国绿色能源开发的重要领域。尽管北美页岩气“革命”取得了成功，目前也仅有预期产量5%~15%的采收率。与北美地区相比，中国页岩气埋藏深，赋存条件差，自然丰度低，因此，高效开采面临更多的困难和挑战。近年来，围绕国家重大能源战略需求，瞄准技术发展前沿，学术界和工业界联合对页岩气高效开采的关键科学和技术问题展开研究。本文结合近三年四川、重庆地区的页岩气试验区块遇到的新问题，针对中国未来3 500 m以下深部开采的新挑战，如地质沉积、裂缝发育构造不同、上覆压力增加、水平应力场变化等新问题，介绍和总结了目前中国页岩气高效开采面临的力学科学问题，主要包括多重耦合下的安全优质钻完井力学理论和方法、水力压裂体积改造和多尺度缝网形成机制、多尺度渗流力学特性与解吸附机理等。“深部页岩气高效开采”的研究面向国家重大能源需求，科学意义重大，工程背景明确，需要工程力学、石油工程、地球物理、化学工程和环境工程等多学科专家合作，开展理论研究、物理模拟、数值模拟及现场试验等综合应用基础研究，取得高效开采页岩油气理论与技术的突破。学科交叉是研究页岩气高效开采问题、突破技术瓶颈的桥梁，只有力学与石油工程、地球科学等学科实现深度交叉融合，才能更加有效地推动页岩油气等非常规油气资源的开发。
页岩气是指赋存于富含有机质泥页岩中以吸附和游离状态为主要存在方式的天然气，中国资源量丰富，地域分布广泛。页岩气开采能缓解我国常规油气产量不足、煤化石燃料引起环境污染等问题，已成为中国绿色能源开发的重要领域。尽管北美页岩气“革命”取得了成功，目前也仅有预期产量5%~15%的采收率。与北美地区相比，中国页岩气埋藏深，赋存条件差，自然丰度低，因此，高效开采面临更多的困难和挑战。近年来，围绕国家重大能源战略需求，瞄准技术发展前沿，学术界和工业界联合对页岩气高效开采的关键科学和技术问题展开研究。本文结合近三年四川、重庆地区的页岩气试验区块遇到的新问题，针对中国未来3 500 m以下深部开采的新挑战，如地质沉积、裂缝发育构造不同、上覆压力增加、水平应力场变化等新问题，介绍和总结了目前中国页岩气高效开采面临的力学科学问题，主要包括多重耦合下的安全优质钻完井力学理论和方法、水力压裂体积改造和多尺度缝网形成机制、多尺度渗流力学特性与解吸附机理等。“深部页岩气高效开采”的研究面向国家重大能源需求，科学意义重大，工程背景明确，需要工程力学、石油工程、地球物理、化学工程和环境工程等多学科专家合作，开展理论研究、物理模拟、数值模拟及现场试验等综合应用基础研究，取得高效开采页岩油气理论与技术的突破。学科交叉是研究页岩气高效开采问题、突破技术瓶颈的桥梁，只有力学与石油工程、地球科学等学科实现深度交叉融合，才能更加有效地推动页岩油气等非常规油气资源的开发。
2012, 44(2): 269-277.
doi: 10.6052/0459-1879-2012-2-20120210
Abstract:
2012, 44(2): 252-258.
doi: 10.6052/0459-1879-2012-2-20120208
Abstract:
