Numerical simulation based on two-directional freeze and thaw algorithm for thermal diffusion model

Freeze-thaw processes significantly modulate hydraulic and thermal char- acteristics of soil. The changes in the frost and thaw fronts （FTFs） affect the water and energy cycles between the land surface and the atmosphere. Thus, the frozen soil com- prising permafrost and seasonally frozen soil has important effects on the land surface hydrology in cold regions. In this study, a two-directional freeze and thaw algorithm is incorporated into a thermal diffusion equation for simulating FTFs. A local adaptive variable-grid method is used to discretize the model. Sensitivity tests demonstrate that the method is stable and FTFs can be tracked continuously. The FTFs and soil tempera- ture at the Qinghai-Tibet Plateau D66 site are simulated hourly from September 1, 1997 to September 22, 1998. The results show that the incorporated model performs much better in the soil temperature simulation than the original thermal diffusion equation, showing potential applications of the method in land-surface process modeling.

CHARACTERISTIC GALERKIN METHOD FOR CONVECTION-DIFFUSION EQUATIONS AND IMPLICIT ALGORITHM USING PRECISE INTEGRATION

This paper presents a finite element procedure for solving transient, multidimensional convection-diffusion equations. The procedure is based on the characteristic Galerkin method with an implicit algorithm using precise integration method. With the operator splitting procedure, the precise integration method is introduced to determine the material derivative in the convection-diffusion equation, consequently, the physical quantities of material points. An implicit algorithm with a combination of both the precise and the traditional numerical integration procedures in time domain in the Lagrange coordinates for the characteristic Galerkin method is formulated. The stability analysis of the algorithm shows that the unconditional stability of present implicit algorithm is enhanced as compared with that of the traditional implicit numerical integration procedure. The numerical results validate the presented method in solving convection-diffusion equations. As compared with SUPG method and explicit characteristic Galerkin method, the present method gives the results with higher accuracy and better stability.

Distributed Secondary Control Based on Dynamic Diffusion Algorithm for Current Sharing and Average Voltage Regulation in DC Microgrids

This paper introduces a distributed secondary control scheme for achieving current sharing and average voltage regulation objectives in a DC microgrid.The proposed scheme employs a dynamic diffusion algorithm(DDA)instead of the consensus algorithm to enable distributed communication among converters.To help understand DDA,the relation of DDA and other diffusion algorithms is discussed in detail and its superiority is shown by comparison with diffusion and consensus algorithms.Furthermore,considering the discrete nature and different sampling time of the digital controller and communication network,a z-domain model of the entire DC microgrid is established.The influence of communication and secondary control parameters on the system stability is investigated.Based on the established model,the tolerable communication rates are obtained.Real-time simulations conducted on the OPAL-RT platform validate the effectiveness of the proposed scheme,showcasing its advantages in terms of convergence speed and stability.

A robust tensor watermarking algorithm for diffusion-tensor images

Watermarking algorithms that use convolution neural networks have exhibited good robustness in studies of deep learning networks.However,after embedding watermark signals by convolution,the feature fusion eficiency of convolution is relatively low;this can easily lead to distortion in the embedded image.When distortion occurs in medical images,especially in diffusion tensor images(DTIs),the clinical value of the DTI is lost.To address this issue,a robust watermarking algorithm for DTIs implemented by fusing convolution with a Transformer is proposed to ensure the robustness of the watermark and the consistency of sampling distance,which enhances the quality of the reconstructed image of the watermarked DTIs after embedding the watermark signals.In the watermark-embedding network,Ti-weighted(Tlw)images are used as prior knowledge.The correlation between T1w images and the original DTI is proposed to calculate the most significant features from the T1w images by using the Transformer mechanism.The maximum of the correlation is used as the most significant feature weight to improve the quality of the reconstructed DTI.In the watermark extraction network,the most significant watermark features from the watermarked DTI are adequately learned by the Transformer to robustly extract the watermark signals from the watermark features.Experimental results show that the average peak signal-to-noise ratio of the watermarked DTI reaches 50.47 dB,the diffusion characteristics such as mean diffusivity and fractional anisotropy remain unchanged,and the main axis deflection angleαAc is close to 1.Our proposed algorithm can effectively protect the copyright of the DTI and barely affects the clinical diagnosis.

Diffusion mechanism simulation of cloud manufacturing complex network based on cooperative game theory

Cloud manufacturing is a specific implementation form of the "Internet + manufacturing" strategy. Why and how to develop cloud manufacturing platform(CMP), however, remains the key concern of both platform operators and users. A microscopic model is proposed to investigate advantages and diffusion forces of CMP through exploration of its diffusion process and mechanism. Specifically, a three-stage basic evolution process of CMP is innovatively proposed. Then, based on this basic process, a more complex CMP evolution model has been established in virtue of complex network theory, with five diffusion forces identified. Thereafter, simulations on CMP diffusion have been conducted. The results indicate that, CMP possesses better resource utilization,user satisfaction, and enterprise utility. Results of simulation on impacts of different diffusion forces show that both the time required for CMP to reach an equilibrium state and the final network size are affected simultaneously by the five diffusion forces. All these analyses indicate that CMP could create an open online cooperation environment and turns out to be an effective implementation of the "Internet + manufacturing" strategy.

INTERPOLATION TECHNIQUE FOR SPARSE DATA BASED ON INFORMATION DIFFUSION PRINCIPLE-ELLIPSE MODEL

Addressing the difficulties of scattered and sparse observational data in ocean science,a new interpolation technique based on information diffusion is proposed in this paper.Based on a fuzzy mapping idea,sparse data samples are diffused and mapped into corresponding fuzzy sets in the form of probability in an interpolation ellipse model.To avoid the shortcoming of normal diffusion function on the asymmetric structure,a kind of asymmetric information diffusion function is developed and a corresponding algorithm-ellipse model for diffusion of asymmetric information is established.Through interpolation experiments and contrast analysis of the sea surface temperature data with ARGO data,the rationality and validity of the ellipse model are assessed.

Time-frequency analysis of Li solid-phase diffusion in spherical active particles under typical discharge modes

Li transient concentration distribution in spherical active material particles can affect the maximum power density and the safe operating regime of the electric vehicles(EVs). On one hand, the quasiexact/exact solution obtained in the time/frequency domain is time-consuming and just as a reference value for approximate solutions;on the other hand, calculation errors and application range of approximate solutions not only rely on approximate algorithms but also on discharge modes. For the purpose to track the transient dynamics for Li solid-phase diffusion in spherical active particles with a tolerable error range and for a wide applicable range, it is necessary to choose optimal approximate algorithms in terms of discharge modes and the nature of active material particles. In this study, approximation methods,such as diffusion length method, polynomial profile approximation method, Padé approximation method,pseudo steady state method, eigenfunction-based Galerkin collocation method, and separation of variables method for solving Li solid-phase diffusion in spherical active particles are compared from calculation fundamentals to algorithm implementation. Furthermore, these approximate solutions are quantitatively compared to the quasi-exact/exact solution in the time/frequency domain under typical discharge modes, i.e., start-up, slow-down, and speed-up. The results obtained from the viewpoint of time-frequency analysis offer a theoretical foundation on how to track Li transient concentration profile in spherical active particles with a high precision and for a wide application range. In turn, optimal solutions of Li solid diffusion equations for spherical active particles can improve the reliability in predicting safe operating regime and estimating maximum power for automotive batteries.

Numerical Simulation of Superplastic Forming and Diffusion Bonding of Ti Alloys

The research on numerical simulation for combinative process of SPF/DB is carried out in this paper. The contacting problem of sheets is analyzed by using the penalty method. In order to solve the contact problem of different parts of the sheet, a new algorithm for contacting judgment is proposed. According to the relation of the distance vector and the vector of contacting element area, and the condition of contact, it can be judged whether or not a node on the slave surface and the corresponding master surface are in the state of SPF/DB. The Mindlin shell element is employed to simulate SPF/DB process of an asymmetry double-cell cup of Ti-6Al-4V to examine the efficiency of the new algorithm using ARVIP-3D. The results of the numerical simulation are in good agreement with experimental results.

An Explicit-Implicit Predictor-Corrector Domain Decomposition Method for Time Dependent Multi-Dimensional Convection Diffusion Equations

The numerical solution of large scale multi-dimensional convection diffusion equations often requires efficient parallel algorithms.In this work,we consider the extension of a recently proposed non-overlapping domain decomposition method for two dimensional time dependent convection diffusion equations with variable coefficients. By combining predictor-corrector technique,modified upwind differences with explicitimplicit coupling,the method under consideration provides intrinsic parallelism while maintaining good stability and accuracy.Moreover,for multi-dimensional problems, the method can be readily implemented on a multi-processor system and does not have the limitation on the choice of subdomains required by some other similar predictor-corrector or stabilized schemes.These properties of the method are demonstrated in this work through both rigorous mathematical analysis and numerical experiments.

Influence Maximization for Cascade Model with Diffusion Decay in Social Networks

Maximizing the spread of influence is to select a set of seeds with specified size to maximize the spread of influence under a certain diffusion model in a social network. In the actual spread process, the activated probability of node increases with its newly increasing activated neighbors, which also decreases with time. In this paper, we focus on the problem that selects k seeds based on the cascade model with diffusion decay to maximize the spread of influence in social networks. First, we extend the independent cascade model to incorporate the diffusion decay factor, called as the cascade model with diffusion decay and abbreviated as CMDD. Then, we discuss the objective function of maximizing the spread of influence under the CMDD, which is NP-hard. We further prove the monotonicity and submodularity of this objective function. Finally, we use the greedy algorithm to approximate the optimal result with the ration of 1 ? 1/e.

AN ASYMPTOTIC BEHAVIOR AND A POSTERIORI ERROR ESTIMATES FOR THE GENERALIZED SCHWARTZ METHOD OF ADVECTION-DIFFUSION EQUATION

In this paper, a posteriori error estimates for the generalized Schwartz method with Dirichlet boundary conditions on the interfaces for advection-diffusion equation with second order boundary value problems are proved by using the Euler time scheme combined with Galerkin spatial method. Furthermore, an asymptotic behavior in Sobolev norm is de- duced using Benssoussau-Lions＇ algorithm. Finally, the results of some numerical experiments are presented to support the theory.

多因素优化蚁群算法机器人路径规划

采用传统蚁群算法进行路径规划中,存在收敛速度慢,路径不平滑,方向性与目的性较差等问题,提出了多因素优化蚁群算法以提高路径寻优的性能。应用扩散方式赋予地图不均匀的初始信息素,为路径搜索提供更好的方向性,避免了局部最优解的出现;距离启发信息、障碍物阻力启发信息和路径角度启发信息作为综合启发信息应用于蚁群算法,增强蚂蚁移动的目的性,缩短路径长度;运用贝塞尔曲线优化路径上的拐点处,输出平滑路径。仿真结果表明,多因素优化蚁群算法应对多样性环境具有更强的适应性,有效避免了局部最优解,规划出的最优路径更短且光滑,有利于机器人流畅通行,更具有工程实践意义。

面向栅格地图的区域渐进均分算法

单架无人机续航能力限制了区域全覆盖侦察,合理的区域划分是实现多无人机协同全域侦察的关键。栅格法规划侦察区域是无人机区域侦察的常用研究方法。为了解决栅格地图等量划分的问题,提出了一种面向栅格地图的区域渐进均分算法。算法由4个阶段构成。阶段1,建立区域边界确认的跳跃迭代法,根据栅格的特点制定判定条件,进行栅格特征标识。阶段2,提出一种双特征标识方法,对射线法进行改进,确定区域内部栅格。阶段3,模仿水波扩散,提出了一种邻边扩散法,实现区域初步的扩散分割。阶段4,设计补偿规则,通过邻边补偿算法,对各子区域栅格数进行数量补偿。实验证明,区域渐进均分算法相较于其他算法,具有较好的聚集性,连续性和均匀性,为多无人机协同全域侦察提供了理论保证。

舰船管路布置PG-MACO优化方法

针对舰船管路设计效率低下的问题提出一种管路布置优化方法.综合考虑安全性、经济性、协调性和可操作性等工程背景建立优化数学模型,改进蚁群算法在处理混合管路布置工况下的缺陷,提出优化可行解搜索的空间状态转移策略,提升信息素启发效果并加速算法收敛的信息素扩散机制,面向混合管路布置工况设计多蚁群协同进化机制.基于二次开发技术实现本方法在第三方设计软件上的应用,采用核级一回路管道布置工程案例进行验证.结果表明信息素高斯扩散多蚁群优化(PG-MACO)算法的性能和布置效果优于传统蚁群算法,寻路效率提升58.38%,收敛代数缩短43.24%,布置结果中管路长度缩短33.88%,管路折弯次数减少41.67%,验证了本方法的有效性和工程实用性.

面向社交网络重要信息传播的重叠节点挖掘模型研究

针对动态社交网络中的社区检测问题,提出一种面向社交网络重要信息传播的重叠节点挖掘模型(SNONMM),结合标签传播算法(LPA)和扩散激活原理,实现对动态社交网络中重叠社区的高效检测.该模型的新节点在社交网络中向其他节点传播其标签的机会大于旧节点,从而使新节点更容易被发现并纳入相应的社区.同时,引入激活值来表示每个标签的传播强度,有助于更准确地捕捉社区结构的变化.为了验证该方法的有效性,通过两个真实数据集和一个人工合成网络对其性能进行评估.实验结果表明,该方法在检测社区准确性方面优于其他可用方法.

基于改进ORB算法的特征检测与匹配研究

针对传统ORB算法中阙值选取不具有普适性,易受光照影响,纹理信息提取能力弱且特征点易产生富集情况的缺陷,提出改进的ORB特征提取与匹配算法。首先以待检测点为中心进行区域划分,其次利用自适应阙值判断待检测点,并使用自适应范围的非极大抑制算法解决特征点富集问题,提高均匀性。然后使用各项异性扩散滤波提高纹理信息提取能力,最后结合双边滤波改进描述子点对,结合PROSAC算法消除误匹配。实验结果表明,改进后的算法对光照有较强的适应能力,提高了纹理特征提取的能力,特征点分布均匀,改善了富集效应,光照条件下的匹配精度得到提高,具有更好的适应能力。

考虑隐私保护和去中心化的分布式能源交易模式研究

为了缓解配电网分布式能源交易市场存在的计算压力大、个人隐私难以保护和抗干扰能力弱等问题,设计了一个考虑隐私保护和去中心化的分布式能源交易模式。首先,以社会福利最大化为目标构建了一个集中式的统一优化模型。然后,基于梯度上升和对偶分解方法对集中式模型进行分解,得到了相应的分布式的优化模型。进一步采用扩散策略,提出了一种基于组合适应的共识算法,旨在不引入市场组织者的情况下,仅通过主体间传递交易电价和供需不平衡电量等部分信息来实现市场的最优出清,并同时保护市场主体的个人隐私和减轻计算压力。最后,算例分析验证了该交易模式的有效性,以及在新能源出力不确定、市场主体加入退出等因素影响下的鲁棒性和可拓展性。

基于膜计算的扩散优化算法及工程应用

文中提出一种全局优化算法,称为基于膜计算的扩散优化算法(MC-DOA).该算法受到叶绿体和线粒体双膜细胞结构以及粒子扩散现象的启发,利用一个混合膜结构系统和四种不同的粒子搜索策略来寻找全局最优值.选取了两类基准测试函数对MC-DOA的性能进行测试试验,结果表明:MC-DOA能够精确快速的找到测试函数的最优值.将MC-DOA应用到实际工程问题——船舶螺旋桨参数优化设计当中,结果显示MC-DOA能够通过对螺旋桨参数的优化,有效地提高螺旋桨的敞水效率,表明了MC-DOA在船舶优化设计领域的适用性和有效性.

基于超混沌系统及有限域的图像加密算法

混沌系统由于其自身的混沌特性,被广泛应用于安全通信领域;但近年来,低维的混沌系统存在退化现象、密钥空间小等问题,应用于图像加密其安全性能并不高.为了提高混沌系统的复杂性,从相图、平衡点、Lyapunov指数谱、分岔图以及谱熵复杂度等方面探究了一个四维超混沌系统的动力学特性.分析结果表明,该系统能够在较大的参数范围内展示出混沌现象,且在一定的参数范围内有2个正的Lyapunov指数,进一步证实该系统为超混沌系统,从而基于该系统和有限域理论设计了一个加密算法.在加密过程中先用2次置乱对图像进行预处理,再基于有限域进行扩散以达到加密的目的.安全性实验结果证明该加密方案安全性能较高,可以抵抗常见的攻击.

基于动态扩散算法的直流微电网简化分布式二层控制

孤岛直流微电网采用下垂控制实现电流均分时,均流效果受馈线阻抗影响且带来电压跌落。为实现电压恢复和电流精确均分,提出了一种采用动态扩散算法的简化分布式二层控制策略。相比于传统二层控制,该简化二层控制策略仅包含1台积分控制器和1个通信变量,简化了控制结构,减轻了通信链路负担。策略采用动态扩散算法进行分布式通信,改善了系统的收敛速度以及稳定性。考虑到不可忽略通信采样时间对系统稳定性的影响,建立了系统的离散时间小信号模型,绘制根轨迹图分析了二层控制增益和通信采样周期等关键参数对系统稳定性的影响。最后,基于MATLAB/Simulink的仿真结果验证了所提策略在动态性能和稳定性上的优越性。