Computational fluid dynamics-discrete element method simulation of stirred tank reactor for graphene production

Liquid phase exfoliation(LPE)process for graphene production is usually carried out in stirred tank reactor and the interactions between the solvent and the graphite particles are important as to improve the production efficiency.In this paper,these interactions were revealed by computational fluid dynamics–discrete element method(CFD-DEM)method.Based on simulation results,both liquid phase flow hydrodynamics and particle motion behavior have been analyzed,which gave the general information of the multiphase flow behavior inside the stirred tank reactor as to graphene production.By calculating the threshold at the beginning of graphite exfoliation process,the shear force from the slip velocity was determined as the active force.These results can support the optimization of the graphene production process.

MatDEM-fast matrix computing of the discrete element method

Discrete element method can effectively simulate the discontinuity,inhomogeneity and large deformation and failure of rock and soil.Based on the innovative matrix computing of the discrete element method,the highperformance discrete element software MatDEM may handle millions of elements in one computer,and enables the discrete element simulation at the engineering scale.It supports heat calculation,multi-field and fluidsolid coupling numerical simulations.Furthermore,the software integrates pre-processing,solver,postprocessing,and powerful secondary development,allowing recompiling new discrete element software.The basic principles of the DEM,the implement and development of the MatDEM software,and its applications are introduced in this paper.The software and sample source code are available online(http://matdem.com).

A Single Image Derain Method Based on Residue Channel Decomposition in Edge Computing

The numerous photos captured by low-price Internet of Things(IoT)sensors are frequently affected by meteorological factors,especially rainfall.It causes varying sizes of white streaks on the image,destroying the image texture and ruining the performance of the outdoor computer vision system.Existing methods utilise training with pairs of images,which is difficult to cover all scenes and leads to domain gaps.In addition,the network structures adopt deep learning to map rain images to rain-free images,failing to use prior knowledge effectively.To solve these problems,we introduce a single image derain model in edge computing that combines prior knowledge of rain patterns with the learning capability of the neural network.Specifically,the algorithm first uses Residue Channel Prior to filter out the rainfall textural features then it uses the Feature Fusion Module to fuse the original image with the background feature information.This results in a pre-processed image which is fed into Half Instance Net(HINet)to recover a high-quality rain-free image with a clear and accurate structure,and the model does not rely on any rainfall assumptions.Experimental results on synthetic and real-world datasets show that the average peak signal-to-noise ratio of the model decreases by 0.37 dB on the synthetic dataset and increases by 0.43 dB on the real-world dataset,demonstrating that a combined model reduces the gap between synthetic data and natural rain scenes,improves the generalization ability of the derain network,and alleviates the overfitting problem.

Complementary memtransistors for neuromorphic computing: How, what and why

Memtransistors in which the source-drain channel conductance can be nonvolatilely manipulated through the gate signals have emerged as promising components for implementing neuromorphic computing.On the other side,it is known that the complementary metal-oxide-semiconductor(CMOS)field effect transistors have played the fundamental role in the modern integrated circuit technology.Therefore,will complementary memtransistors(CMT)also play such a role in the future neuromorphic circuits and chips?In this review,various types of materials and physical mechanisms for constructing CMT(how)are inspected with their merits and need-to-address challenges discussed.Then the unique properties(what)and poten-tial applications of CMT in different learning algorithms/scenarios of spiking neural networks(why)are reviewed,including super-vised rule,reinforcement one,dynamic vision with in-sensor computing,etc.Through exploiting the complementary structure-related novel functions,significant reduction of hardware consuming,enhancement of energy/efficiency ratio and other advan-tages have been gained,illustrating the alluring prospect of design technology co-optimization(DTCO)of CMT towards neuro-morphic computing.

Fast and Accurate Predictor-Corrector Methods Using Feedback-Accelerated Picard Iteration for Strongly Nonlinear Problems

Although predictor-corrector methods have been extensively applied,they might not meet the requirements of practical applications and engineering tasks,particularly when high accuracy and efficiency are necessary.A novel class of correctors based on feedback-accelerated Picard iteration(FAPI)is proposed to further enhance computational performance.With optimal feedback terms that do not require inversion of matrices,significantly faster convergence speed and higher numerical accuracy are achieved by these correctors compared with their counterparts;however,the computational complexities are comparably low.These advantages enable nonlinear engineering problems to be solved quickly and accurately,even with rough initial guesses from elementary predictors.The proposed method offers flexibility,enabling the use of the generated correctors for either bulk processing of collocation nodes in a domain or successive corrections of a single node in a finite difference approach.In our method,the functional formulas of FAPI are discretized into numerical forms using the collocation approach.These collocated iteration formulas can directly solve nonlinear problems,but they may require significant computational resources because of the manipulation of high-dimensionalmatrices.To address this,the collocated iteration formulas are further converted into finite difference forms,enabling the design of lightweight predictor-corrector algorithms for real-time computation.The generality of the proposed method is illustrated by deriving new correctors for three commonly employed finite-difference approaches:the modified Euler approach,the Adams-Bashforth-Moulton approach,and the implicit Runge-Kutta approach.Subsequently,the updated approaches are tested in solving strongly nonlinear problems,including the Matthieu equation,the Duffing equation,and the low-earth-orbit tracking problem.The numerical findings confirm the computational accuracy and efficiency of the derived predictor-corrector algorithms.

A novel box-counting method for quantitative fractal analysis of threedimensional pore characteristics in sandstone

Fractal theory offers a powerful tool for the precise description and quantification of the complex pore structures in reservoir rocks,crucial for understanding the storage and migration characteristics of media within these rocks.Faced with the challenge of calculating the three-dimensional fractal dimensions of rock porosity,this study proposes an innovative computational process that directly calculates the three-dimensional fractal dimensions from a geometric perspective.By employing a composite denoising approach that integrates Fourier transform(FT)and wavelet transform(WT),coupled with multimodal pore extraction techniques such as threshold segmentation,top-hat transformation,and membrane enhancement,we successfully crafted accurate digital rock models.The improved box-counting method was then applied to analyze the voxel data of these digital rocks,accurately calculating the fractal dimensions of the rock pore distribution.Further numerical simulations of permeability experiments were conducted to explore the physical correlations between the rock pore fractal dimensions,porosity,and absolute permeability.The results reveal that rocks with higher fractal dimensions exhibit more complex pore connectivity pathways and a wider,more uneven pore distribution,suggesting that the ideal rock samples should possess lower fractal dimensions and higher effective porosity rates to achieve optimal fluid transmission properties.The methodology and conclusions of this study provide new tools and insights for the quantitative analysis of complex pores in rocks and contribute to the exploration of the fractal transport properties of media within rocks.

Computing methods for icosahedral and symmetry-mismatch reconstruction of viruses by cryo-electron microscopy

Three-dimensional（3 D） reconstruction of icosahedral viruses has played a crucial role in the development of cryoelectron microscopy single-particle reconstruction, with many cryo-electron microscopy techniques first established for structural studies of icosahedral viruses, owing to their high symmetry and large mass. This review summarizes the computational methods for icosahedral and symmetry-mismatch reconstruction of viruses, as well as the likely challenges and bottlenecks in virus reconstruction, such as symmetry mismatch reconstruction, contrast transformation function（CTF）correction, and particle distortion.

Extended multiscale finite element method for mechanical analysis of heterogeneous materials

An extended multiscale finite element method （EMsFEM） is developed for solving the mechanical problems of heterogeneous materials in elasticity.The underlying idea of the method is to construct numerically the multiscale base functions to capture the small-scale features of the coarse elements in the multiscale finite element analysis.On the basis of our existing work for periodic truss materials, the construction methods of the base functions for continuum heterogeneous materials are systematically introduced. Numerical experiments show that the choice of boundary conditions for the construction of the base functions has a big influence on the accuracy of the multiscale solutions, thus,different kinds of boundary conditions are proposed. The efficiency and accuracy of the developed method are validated and the results with different boundary conditions are verified through extensive numerical examples with both periodic and random heterogeneous micro-structures.Also, a consistency test of the method is performed numerically. The results show that the EMsFEM can effectively obtain the macro response of the heterogeneous structures as well as the response in micro-scale,especially under the periodic boundary conditions.

Comparison of SCS and Green-Ampt Methods in Surface Runoff-Flooding Simulation for Klang Watershed in Malaysia

The main aim in this research is comparison the parameters of some storm events in the watershed using two loss models in Unit hydrograph method by HEC-HMS. SCS Curve Number and Green-Ampt methods by developing loss model as a major component in runoff and flood modeling. The study is conducted in the Kuala Lumpurwatershed with674 km2 area located in Klang basin inMalaysia. The catchment delineation is generated for the Klang watershed to get sub-watershed parameters by using HEC-GeoHMS extension in ARCGIS. Then all the necessary parameters are assigned to the models applied in this study to run the runoff and flood model. The results showed that there was no significant difference between the SCS-CN and Green-Ampt loss method applied in the Klang watershed. Estimated direct runoff and Peak discharge (r = 0.98) indicates a statistically positive correlations between the results of the study. And also it has been attempted to use objective functions in HEC-HMS (percent error peaks and percent error volume) to classify the methods. The selection of best method is on the base of considering least difference between the results of simulation to observed events in hydrographs so that it can address which model is suit for runoff-flood simulation in Klang watershed. Results showed that SCS CN and Green-Ampt methods, in three events by fitting with percent error in peak and percent error in volume had no significant difference.

Application of GIS-based SCS-CN method in West Bank catchments,Palestine

Among the most basic challenges of hydrology are the prediction and quantification of catchment surface runoff. The runoff curve number （CN） is a key factor in determining runoff in the SCS （Soil Conservation Service） based hydrologic modeling method. The traditional SCS-CN method for calculating the composite curve number is very tedious and consumes a major portion of the hydrologic modeling time. Therefore, geographic information systems （G/S） are now being used in combination with the SCS-CN method. This paper assesses the modeling of flow in West Bank catchments using the GIS-based SCS-CN method. The West Bank, Palestine, is characterized as an arid to semi-arid region with annual rainfall depths ranging between 100 mm in the vicinity of the Jordan River to 700 mm in the mountains extending across the central parts of the region. The estimated composite curve number for the entire West Bank is about 50 assuming dry conditions. This paper clearly demonstrates that the integration of GIS with the SCS-CN method provides a powerful tool for estimating runoff volumes in West Bank catchments, representing arid to semi-arid catchments of Palestine.

Object-Oriented Design for FDTD Visual Scientific Computing

A scheme for general purposed FDTD visual scientific computing software is introduced in this paper using object-oriented design (OOD) method. By abstracting the parameters of FDTD grids to an individual class and separating from the iteration procedure, the visual software can be adapted to more comprehensive computing problems. Real-time gray degree graphic and wave curve of the results can be achieved using DirectX technique. The special difference equation and data structure in dispersive medium are considered, and the peculiarity of parameters in perfectly matched layer are also discussed.

A PARALLEL COMPUTATION SCHEME FOR IMPLICIT RUNGE-KUTTA METHODS AND THE ITERATIVELY B-CONVERGENCE OF ITS NEWTON ITERATIVE PROCESS

In this paper, based on the implicit Runge-Kutta(IRK) methods, we derive a class of parallel scheme that can be implemented on the parallel computers with Ns(N is a positive even number) processors efficiently, and discuss the iteratively B-convergence of the Newton iterative process for solving the algebraic equations of the scheme, secondly we present a strategy providing initial values parallelly for the iterative process. Finally, some numerical results show that our parallel scheme is higher efficient as N is not so large.

Dynamic Factor Method of Computing Dynamic Mathematical Model for System Simulation

The computational methods of a typical dynamic mathematical model that can describe the differential element and the inertial element for the system simulation are researched. The stability of numerical solutions of the dynamic mathematical model is researched. By means of theoretical analysis, the error formulas, the error sign criteria and the error relationship criterion of the implicit Euler method and the trapezoidal method are given, the dynamic factor affecting the computational accuracy has been found, the formula and the methods of computing the dynamic factor are given. The computational accuracy of the dynamic mathematical model like this can be improved by use of the dynamic factor.

Effect of a two-phase wedge-sliding model on the ingredient drift of a stable mixed fluid and its computing method

A two-phase wedge-sliding model is developed based on the micro-cellular structure and minimum entropy theory of a stable system, and it is used to describe the ingredient distribution of a mixed fluid in a non-uniform stress field and to analyse its phase drift phenomenon. In the model, the drift-inhibition angle and the expansion-inhibition angle are also deduced and used as evaluating indexes to describe the drifting trend of different ingredients among the mixed fluids. For solving above two indexes of the model, a new calculation method is developed and used to compute the phase distributions of multiphase fluid at peak stress and gradient area stress, respectively. As an example, the flow process of grease in a pipe is analysed by simulation method and used to verify the validity of the model.

A fast computing method to distinguish the hyperbolic trajectory of an non-autonomous system

Attempting to find a fast computing method to DHT （distinguished hyperbolic trajectory）, this study first proves that the errors of the stable DHT can be ignored in normal direction when they are computed as the trajectories extend. This conclusion means that the stable flow with perturbation will approach to the real trajectory as it extends over time. Based on this theory and combined with the improved DHT computing method, this paper reports a new fast computing method to DHT, which magnifies the DHT computing speed without decreasing its accuracy.

A Parallel Computational Scheme on Hybrid Methods

Based on the efficient hybrid methods for solving initial value problems of stiff ODEs, this paper derives a parallel scheme that can be used to solve the problems on parallel computers with N processors, and discusses the iteratively B-convergence of the Newton iterative process, finally, the paper provides some numberical results which show that the parallel scheme is highly efficient as N is not too large.

Highly-Efficient Aerodynamic Optimal Design of Rotor Airfoil Using Viscous Adjoint Method

In order to overcome the efficiency problem of the conventional gradient-based optimal design method,a highly-efficient viscous adjoint-based RANS equations method is applied to the aerodynamic optimal design of hovering rotor airfoil.The C-shaped body-fitted mesh is firstly automatically generated around the airfoil by solving the Poisson equations,and the Navier-Stokes(N-S)equations combined with Spalart-Allmaras(S-A)one-equation turbulence model are used as the governing equations to acquire the reliable flowfield variables.Then,according to multi-constrained characteristics of the optimization of high lift/drag ratio for hovering rotor airfoil,its corresponding adjoint equations,boundary conditions and gradient expressions are newly derived.On these bases,two representative rotor airfoils,NACA0012 airfoil and SC1095 airfoil,are selected as numerical examples to optimize their synthesized aerodynamic characteristics about lift/drag ratio in hover,and better aerodynamic performance of optimal airfoils are obtained compared with the baseline.Furthermore,the new designed rotor with the optimized rotor airfoil has better hover aerodynamic characteristics compared with the baseline rotor.In contrast to the baseline airfoils optimized by the finite difference method,it is demonstrated that the adjoint optimal algorithm itself is practical and highly-efficient for the aerodynamic optimization of hover rotor airfoil.

Computational multiscale methods for granular materials

The fine-scale heterogeneity of granular material is characterized by its polydisperse microstructure with randomness and no periodicity. To predict the mechanical response of the material as the microstructure evolves, it is demonstrated to develop computational multiscale methods using discrete particle assembly-Cosserat continuum modeling in micro- and macro- scales,respectively. The computational homogenization method and the bridge scale method along the concurrent scale linking approach are briefly introduced. Based on the weak form of the Hu-Washizu variational principle, the mixed finite element procedure of gradient Cosserat continuum in the frame of the second-order homogenization scheme is developed. The meso-mechanically informed anisotropic damage of effective Cosserat continuum is characterized and identified and the microscopic mechanisms of macroscopic damage phenomenon are revealed. c 2013 The Chinese Society of Theoretical and Applied Mechanics. [doi： 10.1063/2.1301101]

MIXED COMPATIBLE ELEMENT AND MIXED HYBRID INCOMPATIBLE ELEMENT VARIATIONAL METHODS IN DYNAMICS OF VISCOUS BAROTROPIC FLUIDS

This paper presents and proves the mixed compatible finite element variationalprinciples in dynamics of viscous barotropic fluids. When the principles are proved, itis found that the compatibility conditions of stress can be naturally satisfied. The gene-rallzed variational principles with mixed hybrid incompatible finite elements are alsopresented and proved, and they can reduce the computation of incompatible elements indynamics of viscous barotropic flows.

Comparing Eight Computing Algorithms and Four Consensus Methods to Analyze Relationship between Land Use Pattern and Driving Forces

Although many computing algorithms have been developed to analyze the relationship between land use pattern and driving forces (RLPDF), little has been done to assess and reduce the uncertainty of predictions. In this study, we investigated RLPDF based on 1990, 2005 and 2012 datasets at two spatial scales using eight state-of-the-art single computing algorithms and four consensus methods in Jinjing rive catchment in Hunan Province, China. At the entire catchment scale, the mean AUC values were between 0.715 (ANN) and 0.948 (RF) for the single-algorithms, and from 0.764 to 0.962 for the consensus methods. At the subcatchment scale, the mean AUC values between 0.624 (CTA) and 0.972 (RF) for the single-algorithms, and from 0.758 to 0.979 for the consensus methods. At the subcatchment scale, the mean AUC values were between 0.624 (CTA) and 0.972 (RF) for the single-algorithms, and from 0.758 to 0.979 for the consensus methods. The result suggested that among the eight single computing algorithms, RF performed the best overall for woodland and paddy field;consensus method showed higher predictive performance for woodland and paddy field models than the single computing algorithms. We compared the simulation results of the best - and worst-performing algorithms for the entire catchment in 2012, and found that approximately 72.5% of woodland and 72.4% of paddy field had probabilities of occurrence of less than 0.1, and 3.6% of woodland and 14.5% of paddy field had probabilities of occurrence of more than 0.5. In other words, the simulation errors associated with using different computing algorithms can be up to 14.5% if a probability level of 0.5 is set as the threshold. The results of this study showed that the choice of modeling approaches can greatly affect the accuracy of RLPDF prediction. The computing algorithms for specific RLPDF tasks in specific regions have to be localized and optimized.