The classical discrete element approach(DEM)based on Newtonian dynamics can be divided into two major groups,event-driven methods(EDM)and timedriven methods(TDM).Generally speaking,TDM simulations are suited for cases...The classical discrete element approach(DEM)based on Newtonian dynamics can be divided into two major groups,event-driven methods(EDM)and timedriven methods(TDM).Generally speaking,TDM simulations are suited for cases with high volume fractions where there are collisions between multiple objects.EDM simulations are suited for cases with low volume fractions from the viewpoint of CPU time.A method combining EDM and TDM called Hybrid Algorithm of event-driven and time-driven methods(HAET)is presented in this paper.The HAET method employs TDM for the areas with high volume fractions and EDM for the remaining areas with low volume fractions.It can decrease the CPU time for simulating granular flows with strongly non-uniform volume fractions.In addition,a modified EDM algorithm using a constant time as the lower time step limit is presented.Finally,an example is presented to demonstrate the hybrid algorithm.展开更多
数据驱动建模方法改变了发电机传统的建模范式,导致传统的机电暂态时域仿真方法无法直接应用于新范式下的电力系统。为此,该文提出一种基于数据-模型混合驱动的机电暂态时域仿真(data and physics driven time domain simulation,DPD-T...数据驱动建模方法改变了发电机传统的建模范式,导致传统的机电暂态时域仿真方法无法直接应用于新范式下的电力系统。为此,该文提出一种基于数据-模型混合驱动的机电暂态时域仿真(data and physics driven time domain simulation,DPD-TDS)算法。算法中发电机状态变量与节点注入电流通过数据驱动模型推理计算,并通过网络方程完成节点电压计算,两者交替求解完成仿真。算法提出一种混合驱动范式下的网络代数方程组预处理方法,用以改善仿真的收敛性;算法设计一种中央处理器单元-神经网络处理器单元(central processing unit-neural network processing unit,CPU-NPU)异构计算框架以加速仿真,CPU进行机理模型的微分代数方程求解;NPU作协处理器完成数据驱动模型的前向推理。最后在IEEE-39和Polish-2383系统中将部分或全部发电机替换为数据驱动模型进行验证,仿真结果表明,所提出的仿真算法收敛性好,计算速度快,结果准确。展开更多
A coupled numerical method for the direct numerical simulation of particle-fluid systems is formulated and implemented,resolving an order of magnitude smaller than particle size.The particle motion is described by the...A coupled numerical method for the direct numerical simulation of particle-fluid systems is formulated and implemented,resolving an order of magnitude smaller than particle size.The particle motion is described by the time-driven hard-sphere model,while the hydrodynamic equations governing fluid flow are solved by the lattice Boltzmann method(LBM).Particle-fluid coupling is realized by an immersed boundary method(IBM),which considers the effect of boundary on surrounding fluid as a restoring force added to the governing equations of the fluid.The proposed scheme is validated in the classical flow-around-cylinder simulations,and preliminary application of this scheme to fluidization is reported,demonstrating it to be a promising computational strategy for better understanding complex behavior in particle-fluid systems.展开更多
This article signals the use of Artificial Intelligence (AI) in information security where its merits, downsides as well as unanticipated negative outcomes are noted. It considers AI based models that can strengthen o...This article signals the use of Artificial Intelligence (AI) in information security where its merits, downsides as well as unanticipated negative outcomes are noted. It considers AI based models that can strengthen or undermine infrastructural functions and organize the networks. In addition, the essay delves into AI’s role in Cyber security software development and the need for AI-resilient strategies that could anticipate and thwart AI-created vulnerabilities. The document also touched on the socioeconomic ramifications of the emergence of AI in Cyber security as well. Looking into AI and security literature, the report outlines benefits including made threat detection precision, extended security ops efficiency, and preventive security tasks. At the same time, it emphasizes the positive side of AI, but it also shows potential limitations such as data bias, lack of interpretability, ethical concerns, and security flaws. The work similarly focuses on the characterized of misuse and sophisticated cyberattacks. The research suggests ways to diminish AI-generating maleficence which comprise ethical AI development, robust safety measures and constant audits and updates. With regard to the AI application in Cyber security, there are both pros and cons in terms of socio-economic issues, for example, job displacement, economic growth and the change in the required workforce skills.展开更多
基金supported by a grant from Department of Energy and Process Engineering,Norwegian University of Science and Technology,Institute for Energy Technology(IFE)and SINTEF through the FACE(Multiphase Flow Assurance Innovation Center)project.
文摘The classical discrete element approach(DEM)based on Newtonian dynamics can be divided into two major groups,event-driven methods(EDM)and timedriven methods(TDM).Generally speaking,TDM simulations are suited for cases with high volume fractions where there are collisions between multiple objects.EDM simulations are suited for cases with low volume fractions from the viewpoint of CPU time.A method combining EDM and TDM called Hybrid Algorithm of event-driven and time-driven methods(HAET)is presented in this paper.The HAET method employs TDM for the areas with high volume fractions and EDM for the remaining areas with low volume fractions.It can decrease the CPU time for simulating granular flows with strongly non-uniform volume fractions.In addition,a modified EDM algorithm using a constant time as the lower time step limit is presented.Finally,an example is presented to demonstrate the hybrid algorithm.
基金sponsored by Ministry of Finance under the grant ZDYZ2008-2National Key Science and Technology Project under the grant 2008ZX05014-003-006HZthe Chinese Academy of Sciences under the grant KGCX2-YW-124
文摘A coupled numerical method for the direct numerical simulation of particle-fluid systems is formulated and implemented,resolving an order of magnitude smaller than particle size.The particle motion is described by the time-driven hard-sphere model,while the hydrodynamic equations governing fluid flow are solved by the lattice Boltzmann method(LBM).Particle-fluid coupling is realized by an immersed boundary method(IBM),which considers the effect of boundary on surrounding fluid as a restoring force added to the governing equations of the fluid.The proposed scheme is validated in the classical flow-around-cylinder simulations,and preliminary application of this scheme to fluidization is reported,demonstrating it to be a promising computational strategy for better understanding complex behavior in particle-fluid systems.
文摘This article signals the use of Artificial Intelligence (AI) in information security where its merits, downsides as well as unanticipated negative outcomes are noted. It considers AI based models that can strengthen or undermine infrastructural functions and organize the networks. In addition, the essay delves into AI’s role in Cyber security software development and the need for AI-resilient strategies that could anticipate and thwart AI-created vulnerabilities. The document also touched on the socioeconomic ramifications of the emergence of AI in Cyber security as well. Looking into AI and security literature, the report outlines benefits including made threat detection precision, extended security ops efficiency, and preventive security tasks. At the same time, it emphasizes the positive side of AI, but it also shows potential limitations such as data bias, lack of interpretability, ethical concerns, and security flaws. The work similarly focuses on the characterized of misuse and sophisticated cyberattacks. The research suggests ways to diminish AI-generating maleficence which comprise ethical AI development, robust safety measures and constant audits and updates. With regard to the AI application in Cyber security, there are both pros and cons in terms of socio-economic issues, for example, job displacement, economic growth and the change in the required workforce skills.
