A Sub-element Adaptive Shock Capturing Approach for Discontinuous Galerkin Methods

In this paper,a new strategy for a sub-element-based shock capturing for discontinuous Galerkin(DG)approximations is presented.The idea is to interpret a DG element as a col-lection of data and construct a hierarchy of low-to-high-order discretizations on this set of data,including a first-order finite volume scheme up to the full-order DG scheme.The dif-ferent DG discretizations are then blended according to sub-element troubled cell indicators,resulting in a final discretization that adaptively blends from low to high order within a single DG element.The goal is to retain as much high-order accuracy as possible,even in simula-tions with very strong shocks,as,e.g.,presented in the Sedov test.The framework retains the locality of the standard DG scheme and is hence well suited for a combination with adaptive mesh refinement and parallel computing.The numerical tests demonstrate the sub-element adaptive behavior of the new shock capturing approach and its high accuracy.

Marker-Based and Marker-Less Motion Capturing Video Data: Person and Activity Identification Comparison Based on Machine Learning Approaches

Biomechanics is the study of physiological properties of data and the measurement of human behavior.In normal conditions,behavioural properties in stable form are created using various inputs of subconscious/conscious human activities such as speech style,body movements in walking patterns,writing style and voice tunes.One cannot perform any change in these inputs that make results reliable and increase the accuracy.The aim of our study is to perform a comparative analysis between the marker-based motion capturing system(MBMCS)and the marker-less motion capturing system(MLMCS)using the lower body joint angles of human gait patterns.In both the MLMCS and MBMCS,we collected trajectories of all the participants and performed joint angle computation to identify a person and recognize an activity(walk and running).Using five state of the art machine learning algorithms,we obtained 44.6%and 64.3%accuracy in person identification using MBMCS and MLMCS respectively with an ensemble algorithm(two angles as features).In the second set of experiments,we used six machine learning algorithms to obtain 65.9%accuracy with the k-nearest neighbor(KNN)algorithm(two angles as features)and 74.6%accuracy with an ensemble algorithm.Also,by increasing features(6 angles),we obtained higher accuracy of 99.3%in MBMCS for person recognition and 98.1%accuracy in MBMCS for activity recognition using the KNN algorithm.MBMCS is computationally expensive and if we redesign the model of OpenPose with more body joint points and employ more features,MLMCS(low-cost system)can be an effective approach for video data analysis in a person identification and activity recognition process.

Impact dynamics analysis of free-floating space manipulator capturing satellite on orbit and robust adaptive compound control algorithm design for suppressing motion

The impact dynamics, impact effect, and post-impact unstable motion sup- pression of free-floating space manipulator capturing a satellite on orbit are analyzed. Firstly, the dynamics equation of free-floating space manipulator is derived using the sec- ond Lagrangian equation. Combining the momentum conservation principle, the impact dynamics and effect between the space manipulator end-effector and satellite of the cap- ture process are analyzed with the momentum impulse method. Focusing on the unstable motion of space manipulator due to the above impact effect, a robust adaptive compound control algorithm is designed to suppress the above unstable motion. There is no need to control the free-floating base position to save the jet fuel. Finally, the simulation is proposed to show the impact effect and verify the validity of the control algorithm.

Experimental Research on A New Type of Floating Breakwater for Wave-Absorbing and Energy-Capturing

To avoid the damage caused by big wind and wave in cage culture, and to solve the problem of energy supply faced by automatic breeding equipment, a new type of floating breakwater, named as Savonius double buoy breakwater(SDBB), is proposed in the paper. The floating breakwater is composed of HDPE cylindrical double buoys and horizontal axis Savonius rotors, and has the functions of wave-absorbing and energy-capturing. Based on the linear wave theory and energy conservation law, the Fourier Transform was applied to separate the two-dimensional wave frequency domain, and the energy captured by the rotors and absorbed by the floating breakwater were calculated.Experiments were conducted in a two-dimensional wave-making flume, and the transmitted waves at different wave heights and periods, the tension of mooring lines, and the rotational torque exerted on the Savonius rotor were measured. A series of performance comparison tests were also performed on the new floating breakwater and the traditional double-floating breakwater. Results show that the new floating breakwater is better than the traditional one in terms of reducing wave transmittance, and the combination of the floating breakwater with Savonius rotors can provide for marine aquaculture equipments with green power supply to a certain degree of self-sufficiency.

Multifunctional interlayer with simultaneously capturing and catalytically converting polysulfides for boosting safety and performance of lithium-sulfur batteries at high-low temperatures

Lithium-sulfur(Li-S) batteries as extremely promising high-density energy storage devices have attracted extensive concern. However, practical applications of Li-S batteries are severely restricted by not only intrinsic polysulfides shuttle resulting from their concentration gradient diffusion and sluggish conversion kinetics but also serious safety issue caused by thermolabile and combustible polymer separators.Herein, it is presented for the first time that a robust and multifunctional separator with urchin-like Co-doped Fe OOH microspheres and multiwalled carbon nanotubes(MWCNTs) as an interlayer simultaneously achieves to suppress polysulfides shuttle as well as improves thermotolerance and nonflammability of commercial PP separator. Accordingly, Li-S batteries with modified separator exhibit remarkable performance in a wide range temperatures of-25–100 ℃. Typically, under 25 ℃, ultrahigh initial capacities of 1441 and 827.29 m A h g-1 at 1 C and 2 C are delivered, and remained capacities of 936 and 663.18 mA h g-1 can be obtained after 500 cycles, respectively. At 0.1 C, the S utilization can reach up to 97%. Significantly, at 1 C, the batteries also deliver an excellent performance with remained capacities of high to862.3, 608.4 and 420.6 m A h g-1 after 100, 300 and 450 cycles under 75, 0 and-25 ℃, respectively. This work provides a new insight for developing stable and safe high-performance Li-S batteries.

Assessment of shock capturing schemes for discontinuous Galerkin method

This paper carries out systematical investigations on the performance of several typical shock-capturing schemes for the discontinuous Galerkin （DG） method, including the total variation bounded （TVB） limiter and three artificial diffusivity schemes （the basis function-based （BF） scheme, the face residual-based （FR） scheme, and the element residual-based （ER） scheme）. Shock-dominated flows （the Sod problem, the Shu- Osher problem, the double Mach reflection problem, and the transonic NACA0012 flow） are considered, addressing the issues of accuracy, non-oscillatory property, dependence on user-specified constants, resolution of discontinuities, and capability for steady solutions. Numerical results indicate that the TVB limiter is more efficient and robust, while the artificial diffusivity schemes are able to preserve small-scale flow structures better. In high order cases, the artificial diffusivity schemes have demonstrated superior performance over the TVB limiter.

Gradient-augmented hybrid interface capturing method for incompressible two-phase flow

Motivated by inconveniences of present hybrid methods,a gradient-augmented hybrid interface capturing method（GAHM） is presented for incompressible two-phase flow.A front tracking method（FTM） is used as the skeleton of the GAHM for low mass loss and resources.Smooth eulerian level set values are calculated from the FTM interface,and are used for a local interface reconstruction.The reconstruction avoids marker particle redistribution and enables an automatic treatment of interfacial topology change.The cubic Hermit interpolation is employed in all steps of the GAHM to capture subgrid structures within a single spacial cell.The performance of the GAHM is carefully evaluated in a benchmark test.Results show significant improvements of mass loss,clear subgrid structures,highly accurate derivatives（normals and curvatures） and low cost.The GAHM is further coupled with an incompressible multiphase flow solver,Super CE/SE,for more complex and practical applications.The updated solver is evaluated through comparison with an early droplet research.

The Fuzzy Neural Network Control Scheme With H∞ Tracking Characteristic of Space Robot System With Dual-arm After Capturing a Spin Spacecraft

In this paper,the dynamic evolution for a dualarm space robot capturing a spacecraft is studied,the impact effect and the coordinated stabilization control problem for postimpact closed chain system are discussed.At first,the pre-impact dynamic equations of open chain dual-arm space robot are established by Lagrangian approach,and the dynamic equations of a spacecraft are obtained by Newton-Euler method.Based on the results,with the process of integral and simplify,the response of the dual-arm space robot impacted by the spacecraft is analyzed by momentum conservation law and force transfer law.The closed chain system is formed in the post-impact phase.Closed chain constraint equations are obtained by the constraints of closed-loop geometry and kinematics.With the closed chain constraint equations,the composite system dynamic equations are derived.Secondly,the recurrent fuzzy neural network control scheme is designed for calm motion of unstable closed chain system with uncertain system parameter.In order to overcome the effects of uncertain system inertial parameters,the recurrent fuzzy neural network is used to approximate the unknown part,the control method with H∞tracking characteristic.According to the Lyapunov theory,the global stability is demonstrated.Meanwhile,the weighted minimum-norm theory is introduced to distribute torques guarantee that cooperative operation between manipulators.At last,numerical examples simulate the response of the collision,and the efficiency of the control scheme is verified by the simulation results.

Real-Time Human Body Motion Capturing System

This paper proposes a human body motion capturing system using the depth images. It consists of three processes to estimate the human pose parameters. First, we develop a pixel-based body part classifier to segment the human silhouette into different body part sub-regions and extract the primary joints. Second, we convert the distribution of the joints to the feature vector and apply the regression forest to estimate human pose parameters. Third, we apply the temporal constraints mechanism to find the best human pose parameter with the minimum estimation error. In experiments, we show that our system can operate in real-time with sufficient accuracy.

Capturing surreal life on a sacred glacial mountain

Mount Aragats is an intersection of divinity,science,and living off the land.In Armenia,Mount Aragats looms overhead as a permanent fixture in the sky,a fourpeaked volcano massif that rises from rivers and plains around its base.The mountain is more than just a physical presence:It’s also a divine symbol.Gregory the Illuminator,the patron saint of Armenia who converted

Hydrodynamic Study on Energy Capturing Performance of Horizontal Axis Blades Under Sub-Low Speed Tidal Current

The research on the hydrodynamics of blades is mainly focused on sea areas with high-speed current.However,the average velocity in most territorial waters of China is smaller than 1 m/s,and the lift type of airfoil blades has limited application in most of these conditions.Therefore,it is of great significance to study the tidal current energy capture of blades in sub-low speed sea areas.The effect of flow impact resistance on the blade at sub-low current speed is considered and a new type of thin-walled blade based on the lift type of blade is proposed,and then the lift-impact combined hydrodynamic model of horizontal axis blade is established.Based on this model,and considering the characteristics of tidal current and velocity in the sea area of Yushan Islands,simulation and optimization of blade design are carried out.Additionally,the horizontal axis thin-walled blade and the NACA airfoil contrast blade under the same conditions are developed.By using a synthetical experimental test system,the power,torque,rotational speed and load characteristics of these two blades are tested.The performance of the thin-walled blade and the design theory are verified.It shows that this type of blade has much better energy capture efficiency in the sub-low speed sea area.This research will promote the study and development of turbines that can be used in low-speed current sea areas in the future.

New process development and process evaluation for capturing CO2 in flue gas from power plants using ionic liquid[emim][Tf2N]

Using the ionic liquid[emim][Tf2N]as a physical solvent,it was found by Aspen Plus simulation that it was possible to attempt to capture CO2 from the flue gas discharged from the coal-fired unit of the power plant.Using the combination of model calculation and experimental determination,the density,isostatic heat capacity,viscosity,vapor pressure,thermal conductivity,surface tension and solubility of[emim][Tf2N]were obtained.Based on the NRTL model,the Henry coefficient and NRTL binary interaction parameters of CO2 dissolved in[emim][Tf2N]were obtained by correlating[emim][Tf2N]with the gas–liquid equilibrium data of CO2.Firstly,the calculated relevant data is imported into Aspen Plus,and the whole process model of the ionic liquid absorption process is established.Then the absorption process is optimized according to the temperature distribution in the absorption tower to obtain a new absorption process.Finally,the density,constant pressure heat capacity,surface tension,thermal conductivity,and viscosity of[emim][Tf2N]were changed to investigate the effect of ionic liquid properties on process energy consumption,solvent circulation and heat exchanger design.The results showed that based on the composition of the inlet gas stream to the absorbers,CO2 with a capture rate of 90%and a mass purity higher than 99.5%was captured.These results indicate that the[emim][Tf2N]could be used as a physical solvent for CO2 capture from coal-fired units.In addition,the results will provide a theoretical basis for the design of new ionic liquids for CO2 capture.

Feature-enhanced Model Capturing and Understanding for Rapid Prototyping Application Using Range Imaging

Abstract Models are essential in computer-aided design, manufacturing (CAD/CAM) and concurrent engineering. They are important for object representation, manipulation, and data communication. With fast and explicit availability of 3D object coordinates, range imaging is increasingly used in various engineering applications. We use a laser scanner to digitize object geometry. Model understanding of the digitized range object is therefore a fundamental task in this work. Features are of paramount importance in design and manufacturing contexts, as they are a natural choice for capturing and describing the identity of individual objects, as well as establishing relationships between certain objects. We propose a multi-stage approach to understand range objects. A geometry-based method is developed to evaluate the curvature features of objects in range images. The mapping of the curvature signs is then used to initiate a fuzzy partitioning process in order to extract the quadratic shells. This is followed by a process of qualitative feature identification using a geometric invariance based method. The extracted feature information can be applied to rectify the error introduced during the processes of object scanning and numerical calculation and also can be served to enhance various processes in rapid prototyping application including optimized model re-orientation, etc.

DISCONTINUITY-CAPTURING FINITE ELEMENT COMPUTATION OF UNSTEADY FLOW WITH ADAPTIVE UNSTRUCTURED MESH

A discontinuity-capturing scheme of finite element method(FEM)is proposed.The unstructured-grid technique combined with a new type of adaptive mesh approach is developed for both compressible and incompressible unsteady flows,which exhibits the capability of capturing the shock waves and/or thin shear layers accurately in an unsteady viscous flow at high Reynolds number. In particular,a new testing variable,i.e.,the disturbed kinetic energy E,is suggested and used in the adaptive mesh computation,which is universally applicable to the capturing of both shock waves and shear layers in the inviscid flow and viscous flow at high Reynolds number.Based on several calculated examples,this approach has been proved to be effective and efficient for the calculations of compressible and incompressible flows.

Design and experiment of high-productivity two-stage vacuum pressure swing adsorption process for carbon capturing from dry flue gas

A two-stage vacuum pressure swing adsorption(VPSA)process that coupled kinetically controlled and equilibrium controlled separation process with reflux has been investigated for capturing carbon dioxide from dry flue gas(85%N_(2)/15%CO_(2)).In the first enriching stage,carbon molecular sieve(CMS),which shows kinetic selectivity for CO_(2)/N_(2),is adopted as the adsorbent to remove most N_(2)in feed gas,thereby upgrading CO_(2)and significantly reducing the amount for further refinement.The second stage loads zeolite 13X as adsorbent to purify the CO_(2)-rich flow from the first stage for meeting the requirements of National Energy Technology Laboratory.Series of experiments have been conducted for adsorption isotherms measuring and lab-scale experimental validation as well as analysis.The effect of feed composition on the separation performance of the PSA system was studied experimentally and theoretically here.The optimal results achieved 95.1%purity and 92.9%recovery with a high CO_(2)productivity(1.89 mol CO_(2)·h^(-1)·kg^(-1))and an appropriate energy consumption of 1.07 MJ·(kg CO_(2))^(-1).Further analysis has been carried out by simulation for explicating the temperature,pressure,and concentration distribution at cyclic steady state.

BigEar: Ubiquitous Wireless Low-Budget Speech Capturing Interface

This article presents BigEar, a wireless low-cost speech capturing interface that aims to realize unobtrusive and transparent context-aware vocal interaction for home automation. The speech recognition process implemented in BigEar system considers noise sources including possible holes in the reconstructed audio stream and tries to overcome them by means of inexactness toleration mechanisms to improve intelligibility of the reconstructed signal. Key contribution of this work is the use of extremely low cost devices to realize a modular flexible and real-time wireless sensor network. On-field implementation and experiments show that the proposed solution can perform real-time speech reconstruction, while listening tests confirm the intelligibility of the reconstructed signal.

Lightweight Robot Arm for Capturing Large Space Debris

Effective measures to mitigate space debris are urgently required.Active removal of space debris presents the most effective measures.This study examines a micro robotic satellite with a simple robot arm for active space debris removal.In this study,the details of a proposed active space debris removal system with a robot arm are proposed.The robot arm has flexible joints and a control method to capture the target.The results of feasibility studies,the performance assumed at each step,the prototyping of the capturing robot arm with flexible joints and with a new end-effecter,and their experiment result are presented.

A Discontinuity and Cusp Capturing PINN for Stokes Interface Problems with Discontinuous Viscosity and Singular Forces

In this paper,we present a discontinuity and cusp capturing physicsinformed neural network(PINN)to solve Stokes equations with a piecewiseconstant viscosity and singular force along an interface.We first reformulate the governing equations in each fluid domain separately and replace the singular force effect with the traction balance equation between solutions in two sides along the interface.Since the pressure is discontinuous and the velocity has discontinuous derivatives across the interface,we hereby use a network consisting of two fully-connected sub-networks that approximate the pressure and velocity,respectively.The two sub-networks share the same primary coordinate input arguments but with different augmented feature inputs.These two augmented inputs provide the interface information,so we assume that a level set function is given and its zero level set indicates the position of the interface.The pressure sub-network uses an indicator function as an augmented input to capture the function discontinuity,while the velocity sub-network uses a cusp-enforced level set function to capture the derivative discontinuities via the traction balance equation.We perform a series of numerical experiments to solve two-and three-dimensional Stokes interface problems and perform an accuracy comparison with the augmented immersed interface methods in literature.Our results indicate that even a shallow network with a moderate number of neurons and sufficient training data points can achieve prediction accuracy comparable to that of immersed interface methods.

Adaptive Multi-Resolution Method for 3D Reactive Flows with Level Set Front Capturing

For compressible reactive flows with stiff source terms,a new block-based adaptive multi-resolution method coupled with the adaptive multi-resolution representation model for ZND detonation and a conservative front capturing method based on a level-set technique is presented.When simulating stiff reactive flows,underresolution in space and time can lead to incorrect propagation speeds of discontinuities,and numerical dissipation makes it impossible for traditional shock-capturing methods to locate the detonation front.To solve these challenges,the proposed method leverages an adaptive multi-resolution representation model to separate the scales of the reaction from those of fluid dynamics,achieving both high-resolution solutions and high efficiency.A level set technique is used to capture the detonation front sharply and reduce errors due to the inaccurate prediction of detonation speed.In order to ensure conservation,a conservative modified finite volume scheme is implemented,and the front transition fluxes are calculated by considering a Riemann problem.A series of numerical examples of stiff detonation simulations are performed to illustrate that the present method can acquire the correct propagation speed and accurately capture the sharp detonation front.Comparative numerical results also validate the approach’s benefits and excellent performance.

Biomolecule capturing and sensing on 2D transition metal dichalcogenide canvas

Since the isolation of graphene in 2004,two-dimensional(2D)materials such as transition metal dichalcogenide(TMD)have attracted numerous interests due to their unique van der Waals structure,atomically thin body,and thickness-dependent properties.In recent years,the applications of TMD in public health have emerged due to their large surface area and high surface sensitivities,as well as their unique electrical,optical,and electrochemical properties.In this review,we focus on state-of-the-art methods to modulate the properties of 2D TMD and their applications in biosensing.Particularly,this review provides methods for designing and modulating 2D TMD via defect engineering and morphology control to achieve multi-functional surfaces for molecule capturing and sensing.Furthermore,we compare the 2D TMD-based biosensors with the traditional sensing systems,deepening our understanding of their action mechanism.Finally,we point out the challenges and opportunities of 2D TMD in this emerging area.