CFD Modeling of Active Volume Creation in a Non‐Newtonian Fluid Agitated by Submerged Recirculating Jets

Computational fluid dynamics (CFD) models were employed to investigate flow conditions inside a model reactor in which yield stress non‐Newtonian liquid is mobilized using submerged recirculating jets. The simulation results agree well with the experimental results of active volume in the reactor obtained using flow visualization by the authors in a previous study. The models developed are capable of predicting a critical jet velocity (v_c) that determines the extent of active volume obtained due to jet mixing. The v_c values are influenced both by the rheological properties of the liquid and the nozzle orientation. The liquid with higher effective viscosity leads to higher v_c for a downward facing injection nozzle. However, an upward facing injection nozzle along with a downward facing suction nozzle generates enhanced complementary flow fields which overcome the rheological constraints of the liquid and lead to lower v_c.     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Fulde–Ferrell State in Spin–Orbit-Coupled Superconductor: Application to Dresselhaus SOC

We show that in the presence of magnetic field, two superconducting phases with the center-of-mass momentum of Cooper pair parallel to the magnetic field are induced in Dresselhaus spin–orbit-coupled superconductor. Specifically, at small magnetic field, the center-of-mass momentum is induced due to the energy-spectrum distortion and no unpairing region with vanishing singlet correlation appears. We refer to this superconducting state as the drift-BCS state. By further increasing the magnetic field, the superconducting state falls into the Fulde–Ferrell state with the emergence of the unpairing regions. The observed abrupt enhancement of the center-of-mass momenta and suppression on the order parameters during the transition indicate the occurrence of a first-order phase transition. Enhanced Pauli limit and hence enlarged magnetic-field regime of the Fulde–Ferrell state, due to the spin-flip terms of the spin–orbit coupling, are revealed. We also address the triplet correlations induced by the spin–orbit coupling, and show that the Cooper-pair spin polarizations, generated by the magnetic field and center-of-mass momentum with the triplet correlations exhibit totally different magnetic-field dependences between the drift-BCS and Fulde–Ferrell states.     

Adaptive Finite-time Tracking Control for Class of Uncertain Nonlinearly Parameterized Systems with Input Delay

International Journal of Control, Automation and Systems - In this paper, the tracking problem for a class of uncertain nonlinearly parameterized systems with input delay based the adaptive...     

采煤机行走轮参数化分析软件设计

针对电牵引采煤机渐开线行走轮在ANSYS分析中存在的问题,提出运用APDL语言命令直接建模,并通过VB与ANSYS的交互运行途径,设计了基于VB界面和程序的软件,实现了利用VB界面直接输入参数并调用ANSYS对行走轮自动建模、加载和计算的有限元分析。验证结果表明,该软件减少了设计人员的重复劳动,提高了行走轮的设计效率和水平,具有一定的工程实用价值。