Simulation research on monomer agglomeration of nonmetallic inclusions in steel with a diffusion limited aggregation model

The monomer agglomeration of nonmetallic inclusions was simulated with a diffusion limited aggregation （DLA） model of the fractal theory. The simulation study with a random two-dimensional diffusion was carried out. The results indicate that the DLA model can be used for the simulation of agglomeration behavior of the cluster-type inclusions. The morphology of clusters was observed with SEM and compared with the simulated agglomerates. The modelling procedure of the DLA model is applicable for the agglomeration process. The uncertainty of agglomeration process and the persuasive average agglomerative ratio was analyzed. The factors about the agglomerative ratio with the collision path distance and the size of particles or seed were discussed. The adherence of the nonmetallic inclusions on the dam, the weir and the walls of a tundish, and the absorption of inclusions by stopper or nozzle were also discussed.

Cyber-physical Modeling Technique based Dynamic Aggregation of Wind Farm Considering LVRT Characteristic

With the increasing penetration of wind power,large-scale integrated wind turbine brings stability and security risks to the power grid.For the aggregated modeling of large wind farms,it is crucial to consider low voltage ride-through(LVRT)characteristics.However,in aggregation methods,the approximate neglect behavior is essential,which leads to inevitable errors in the aggregation process.Moreover,the lack of parameters in practice brings new challenges to the modeling of a wind farm.To address these issues,a novel cyber-physical modeling method is proposed.This method not only overcomes the aggregation problem under the black-box wind farm but also accurately realizes the aggregation error fitting according to the operation data.The simulation results reveal that the proposed method can accurately simulate the dynamic behaviors of the wind farm in various scenarios,whether in LVRT mode or normal mode.

Clustered Federated Learning with Weighted Model Aggregation for Imbalanced Data

As a promising edge learning framework in future 6G networks,federated learning(FL)faces a number of technical challenges due to the heterogeneous network environment and diversified user behaviors.Data imbalance is one of these challenges that can significantly degrade the learning efficiency.To deal with data imbalance issue,this work proposes a new learning framework,called clustered federated learning with weighted model aggregation(weighted CFL).Compared with traditional FL,our weighted CFL adaptively clusters the participating edge devices based on the cosine similarity of their local gradients at each training iteration,and then performs weighted per-cluster model aggregation.Therein,the similarity threshold for clustering is adaptive over iterations in response to the time-varying divergence of local gradients.Moreover,the weights for per-cluster model aggregation are adjusted according to the data balance feature so as to speed up the convergence rate.Experimental results show that the proposed weighted CFL achieves a faster model convergence rate and greater learning accuracy than benchmark methods under the imbalanced data scenario.

Four Types of Percolation Transitions in the Cluster Aggregation Network Model

We study the percolation transition in a one-species cluster aggregation network model, in which the parameter α describes the suppression on the cluster sizes. It is found that the model can exhibit four types of percolation transitions, two continuous percolation transitions and two discontinuous ones. Continuous and discontinuous percolation transitions can be distinguished from each other by the largest single jump. Two types of continuous percolation transitions show different behaviors in the time gap. Two types of discontinuous percolation transitions are different in the time evolution of the cluster size distribution. Moreover, we also find that the time gap may also be a measure to distinguish different discontinuous percolations in this model.

A NONCLASSICAL CONSTITUTIVE MODEL FOR CRYSTALPLASTICITY AND ITS APPLICATION

A nonclassical constitutive description for a slip system is formulated by using a simple mechanical model consisting of a spring and a plastic dashpot-like block. The corresponding constitutive model for a single crystal and the analysis for polycrystalline response is proposed based on the KBW's self-consistent theory. The constitutive model contains no yield criterion, so the corresponding numerical analysis is greatly simplified because it involves no additional process to search for the activation of slip systems and slip direction. A mixed averaging approach is proposed to obtain the response of polycrystalline material, which consists of the Gaussian integral mean for the omega which varies continuously within each face of the isosahedron and arithmetic mean for the spatially uniformly distributed twenty sets of 0 and phi determined by the normal of each face of the isosahedron. The main features 316 stainless steel subjected to typical biaxial nonproportional cyclic strain paths are well described. Calculation also shows that the developed model and the corresponding analytical approach are of good accuracy and efficiency.

CONSERVATIVE ESTIMATING FUNCTION IN THE NONLINEAR REGRESSION MODEL WITH AGGREGATED DATA

The purpose of this paper is to study the theory of conservative estimating functions in nonlinear regression model with aggregated data. In this model, a quasi-score function with aggregated data is defined. When this function happens to be conservative, it is projection of the true score function onto a class of estimation functions. By constructing, the potential function for the projected score with aggregated data is obtained, which have some properties of log-likelihood function.

Physical Model of Drying Shrinkage of Recycled Aggregate Concrete

We prepared concretes（RC0, RC30, and RC100） with three different mixes. The poresize distribution parameters of RAC were examined by high-precision mercury intrusion method（MIM） and nuclear magnetic resonance（NMR） imaging. A capillary-bundle physical model with random-distribution pores（improved model, IM） was established according to the parameters, and dry-shrinkage strain values were calculated and verified. Results show that in all pore types, capillary pores, and gel pores have the greatest impacts on concrete shrinkage, especially for pores 2.5-50 and 50-100 nm in size. The median radii are 34.2, 31, and 34 nm for RC0, RC30, and RC100, respectively. Moreover, the internal micropore size distribution of RC0 differs from that of RC30 and RC100, and the pore descriptions of MIM and NMR are consistent both in theory and in practice. Compared with the traditional capillary-bundle model, the calculated results of IM have higher accuracy as demonstrated by experimental verifi cation.

Load Static Models for Conservation Voltage Reduction in the Presence of Harmonics

The Conservation Voltage Reduction (CVR) is a technique that aims to achieve the decrease of power consumption as a result of voltage reduction. The customer is supplied with the lowest possible voltage level compatible with the stipulated level by the regulatory agency. International Standards ANSI C84.1-2006 and IEEE std 1250-1995 specify the range of supply voltage to electronics equipment from 0.9 to 1.05 pu of nominal voltage. To analyse the CVR effect in distribution systems with different load characteristics (residential, commercial, industrial or a combination of these), mathematical load models are used. Typically, these equipment/load models are used to analyse load aggregation without any consideration of its nonlinearity characteristics. Aiming to analyse the nonlinear characteristics and its consequences, this paper presents a discussion of the neglected variables as well as the results of a set of measurements of nonlinear loads. Different mathematical models are applied to obtain them for each load. Using these models the load aggregation is evaluated. It is presented that although the models show adequate results for individual loads, the same does not occur for aggregated models if the harmonic contribution is not considered. Consequently, to apply the load model in CVR it is necessary to consider the harmonics presence and the model has to be done using only the fundamental frequency data. The discussion about the causes is done and the models are compared with the measurements.

A Client Selection Method Based on Loss Function Optimization for Federated Learning

Federated learning is a distributedmachine learningmethod that can solve the increasingly serious problemof data islands and user data privacy,as it allows training data to be kept locally and not shared with other users.It trains a globalmodel by aggregating locally-computedmodels of clients rather than their rawdata.However,the divergence of local models caused by data heterogeneity of different clients may lead to slow convergence of the global model.For this problem,we focus on the client selection with federated learning,which can affect the convergence performance of the global model with the selected local models.We propose FedChoice,a client selection method based on loss function optimization,to select appropriate local models to improve the convergence of the global model.It firstly sets selected probability for clients with the value of loss function,and the client with high loss will be set higher selected probability,which can make them more likely to participate in training.Then,it introduces a local control vector and a global control vector to predict the local gradient direction and global gradient direction,respectively,and calculates the gradient correction vector to correct the gradient direction to reduce the cumulative deviationof the local gradient causedby theNon-IIDdata.Wemake experiments to verify the validity of FedChoice on CIFAR-10,CINIC-10,MNIST,EMNITS,and FEMNIST datasets,and the results show that the convergence of FedChoice is significantly improved,compared with FedAvg,FedProx,and FedNova.

Electric dipolar interaction assisted growth of single crystalline organic thin films

We report on a forest-like-to-desert-like pattern evolution in the growth of an organic thin film observed by using an atomic force microscope. We use a modified diffusion limited aggregation model to simulate the growth process and are able to reproduce the experimental patterns. The energy of electric dipole interaction is calculated and determined to be the driving force for the pattern formation and evolution. Based on these results, single crystalline films are obtained by enhancing the electric dipole interaction while limiting effects of other growth parameters.

Research on the Optimal Aggregation Method of Judgment Matrices Based on Spatial Steiner-Weber Point

This paper is to provide a novel approach for the spatial aggregation of judgment matrices.The optimal aggregation method of judgment matrices based on spatial Steiner-Weber point can effectively aggregate the preference information of group members and achieve the optimization of group preference.The method comprises three key elements:The spatial mapping of the judgment matrices,the spatial optimal aggregation model of the judgment matrices,and the plant growth simulation algorithm(PGSA)is used to find the optimal aggregation points.Firstly,the judgment matrices are mapped into a set of spatial multidimensional coordinates by using spatial mapping rules.Secondly,the spatial Steiner-Weber point is used as the prototype to construct the spatial aggregation model.Thirdly,the PGSA algorithm is used to find the spatial aggregation points,whose spatial weighted Euclidean distance to all the decision makers’preference points is minimal.The optimal aggregation matrix is composed of these optimal aggregation points,which can accurately reflect the decision maker's comprehensive opinions.Finally,the effectiveness and rationality of this method are verified by comparing with the classical group preference aggregation methods.

Parallel computation of seismic analysis of high arch dam

Parallel computation programs are developed for three-dimensional meso-mechanics analysis of fully-graded dam concrete and seismic response analysis of high arch dams （ADs）, based on the Parallel Finite Element Program Generator （PFEPG）. The computational algorithms of the numerical simulation of the meso-structure of concrete specimens were studied. Taking into account damage evolution, static preload, strain rate effect, and the heterogeneity of the meso-structure of dam concrete, the fracture processes of damage evolution and configuration of the cracks can be directly simulated. In the seismic response analysis of ADs, all the following factors are involved, such as the nonlinear contact due to the opening and slipping of the contraction joints, energy dispersion of the far-field foundation, dynamic interactions of the dam-foundation- reservoir system, and the combining effects of seismic action with all static loads. The correctness, reliability and efficiency of the two parallel computational programs are verified with practical illustrations.

Evaluation of global navigation satellite system spoofing efficacy

The spoofing capability of Global Navigation Satellite System(GNSS)represents an important confrontational capability for navigation security,and the success of planned missions may depend on the effective evaluation of spoofing capability.However,current evaluation systems face challenges arising from the irrationality of previous weighting methods,inapplicability of the conventional multi-attribute decision-making method and uncertainty existing in evaluation.To solve these difficulties,considering the validity of the obtained results,an evaluation method based on the game aggregated weight model and a joint approach involving the grey relational analysis and technique for order preference by similarity to an ideal solution(GRA-TOPSIS)are firstly proposed to determine the optimal scheme.Static and dynamic evaluation results under different schemes are then obtained via a fuzzy comprehensive assessment and an improved dynamic game method,to prioritize the deceptive efficacy of the equipment accurately and make pointed improvement for its core performance.The use of judging indicators,including Spearman rank correlation coefficient and so on,combined with obtained evaluation results,demonstrates the superiority of the proposed method and the optimal scheme by the horizontal comparison of different methods and vertical comparison of evaluation results.Finally,the results of field measurements and simulation tests show that the proposed method can better overcome the difficulties of existing methods and realize the effective evaluation.

Prediction of aggregation behavior of submicron-sized particles of praseodymium-doped zirconium silicate in aqueous suspension by population balance model

The aggregation behavior of submicron-sized particles of praseodymium-doped zirconium silicate, a ceramic pigment, in aqueous suspension was predicted by a modified population balance model, In the model, the collision frequencies were selected to describe evolution of the particle size distribution of the suspension. The collision efficiency was estimated as a function of interaction potential between particles based on Derjaguin-Landau-Verwey-Overbeek theory. The population balance model was modified to predict the stable state of the aggregation by introducing the volume mean size of aggregate to stability ratio. In addition, aggregation of the particles in aqueous suspension in the presence of sodium dodecyl benzene sulfonate or potassium chloride was experimentally investigated. The predicted data （i.e., the final aggregate size, aggregation rate, and particle size distribution） were similar to the experimentalresults.

Hydrological Analysis and Ability Assessing of Flood Gating of Karaj Watershed According to the Form of the Watershed

The numeral trait of aquiferous zones in flowage studies and estimations is under most parts of nation. In this study Karaj aquiferous zone in Alborz province was surveyed from the view point of form, the agglomeration of drainage net length of channel and space. The orientation of hillside was specified as the affective factor on creating and streaming the flowage. A flow aggregating hydrological model for the studied zone was prepared and amount of the flow is mostly in which parts of the zone the delay and centralization time in the zone was evaluated and the related diagrams were derived. Finally, the zone was divided into 4 main subzones and their drainage nets were ranked and by 4 factors namely, space, length of canal, drainage aggregation and branch ratio affecting on performance of the zone from the view of from and appearance was surveyed. The factors interfering in SPSS software and their correlations were specified and specific coefficients stand in their related charts. By considering in the zone width and charts it is specified which of the sub zones has the most flowage potential from the view of the zones physical and numeral qualifications. All plots were prepared using GIS and WMS software and the studied zone’s hydrograph was depicted.

Numerical Modeling of Dendrite Growth in Al Alloys

Dendritic grains are the most often observed microstructure in metals and alloys. In the past decade, more and more attention has been paid to the modeling and simulation of dendritic microstructures. This paper describes a modified diffusion-limited aggregation model to simulate the complex shape of the dendrite grains during metal solidification. The fractal model was used to simulate equiaxed dendrite growth. The fractal dimensions of simulated Al alloy structures range from 1.63-1.88 which compares well with the experimentally-measured fractal dimension of 1.85; therefore, the model accurately predicts not only the dendritic structure morphology, but also the fractal dimension of the dendrite structure formed during solidification.

Two-Level Hierarchical PCG Methods for the Quadratic FEM Discretizations of 2D Concrete Aggregate Models

The concrete aggregate model is considered as a type of weakly discontinuous problem consisting of three phases:aggregates which randomly distributed in different shapes,cement paste and internal transition zone(ITZ).Because of different shapes of aggregate and thin ITZs,a huge number of elements are often used in the finite element(FEM)analysis.In order to ensure the accuracy of the numerical solutions near the interfaces,we need to use higher-order elements.The widely used FEM softwares such as ANSYS and ABAQUS all provide the option of quadratic elements.However,they have much higher computational complexity than the linear elements.The corresponding coefficient matrix of the system of equations is a highly ill-conditioned matrix due to the large difference between three phase materials,and the convergence rate of the commonly used solving methods will deteriorate.In this paper,two types of simple and efficient preconditioners are proposed for the system of equations of the concrete aggregate models on unstructured triangle meshes by using the resulting hierarchical structure and the properties of the diagonal block matrices.The main computational cost of these preconditioners is how to efficiently solve the system of equations by using linear elements,and thus we can provide some efficient and robust solvers by calling the existing geometric-based algebraic multigrid(GAMG)methods.Since the hierarchical basis functions are used,we need not present those algebraic criterions to judge the relationships between the unknown variables and the geometric node types,and the grid transfer operators are also trivial.This makes it easy to find the linear element matrix derived directly from the fine level matrix,and thus the overall efficiency is greatly improved.The numerical results have verified the efficiency of the resulting preconditioned conjugate gradient(PCG)methods which are applied to the solution of several typical aggregate models.

Hybrid Control Strategy for Air-conditioning Loads Participating in Peak Load Reduction Through Wide-range Transport Model

This paper proposes a hybrid control strategy of air-conditioning loads(ACLs)for participating in peak load reduction.The hybrid control strategy combines the temperature setpoint adjustment(TSA)control and on/off control together to make full use of response potentials of ACLs.The primary free transport model of ACLs has been established in literature at or near a fixed temperature setpoint.In this paper,a wide-range transport(WRT)model suitable for larger value of TSA is proposed.The WRT model can be constructed easily through the parameter of devices and indoor and outdoor temperature.To modulate the aggregate response characteristics of ACLs more friendly to the power grid,the safe protocol(SP)is adopted and integrated into the WRT model,which achieves a good unification of oscillation suppression and efficient modeling.Moreover,the hybrid control strategy is implemented based on the WRT model,and the model predictive control(MPC)controller is designed considering the tracking error and control switch cost.At last,the superiority of the hybrid control strategy is verified and the performance of ACLs for peak load reduction under this controller is simulated.The simulation results show that the hybrid control strategy could exploit the load reduction potential of ACLs fully than the TSA mode and track the reference signal more accurately.

An adaptive p-FEM for three-dimensional concrete aggregate models

Numerical simulation for concrete aggregate models(CAMs)with different shape aggregates usually requires high accuracy and convergence near the material interfaces.But high memory usage will be needed for those traditional finite element methods such as the method by using mesh refinement throughout the domain.Thus,an adaptive p-version finite element method(p-FEM)is proposed in this paper for the solution of 3D CAM problems,and meanwhile the resulting adaptive computational algorithm and post-processing program are presented.We firstly focused two typical 3D weak discontinuity problems on the influence of different convergence criterions for the computational results of each point on the interface in order to verify the efficiency and convergence of the resulting p-FEM,and then this method is successfully applied to the numerical simulation of CAMs with different shape aggregates.In addition,an efficient hybrid realization method which combines ANSYS and Hypermesh software is also presented in order to quickly establish the geometric models of 3D CAMs.The numerical results have been shown that the proposed p-FEM can efficiently solve the concrete-like particle-reinforced composite problems and more accurate numerical results can be obtained under the case of fewer elements used in simulation of CAMs,even there being some elements with poor quality.

An Efficient Method for Estimating Capability Curve of Virtual Power Plant

To incorporate the operating constraints of a virtual power plant(VPP)in transmission-level operation and market clearing,the concept of the VPP capability curve(VPP-CC)is proposed which explicitly characterizes the allowable range of active and reactive power outputs of a VPP.A two-step projection-based calculation framework is proposed to approximate the VPP-CC by the convex hull of critical points on its perimeter.The output of the proposed algorithm is concise and can be easily incorporated in the existing system operation and market clearing.Case studies based on the IEEE 33 and 123 test feeders show the computational efficiency of the proposed method outperforms existing methods by 4~7 times.Additionally,many fewer inequalities are needed to depict the VPP-CC while achieving the comparative approximation accuracy compared to sampling-based methods,which will relieve the communication and computation burden.