多线程技术在LIA中两路束流测量的实现

强流脉冲电子束作为一种高亮度的光源,具有广阔的应用前景,而双轴束流测量的控制对于研究产生电子束的加速器技术具有重要意义;利用多线程技术在CVI环境下的实现方法,研究了双路束流参数特点、双路束流测量的时序同步控制方法,在此基础上采用线程池多线程技术实现基于TCP/IP的加速器束流测量的数据采集软件;结果表明采用多线程技术可以很好地实现多任务的同时工作,有助于提高束测量的响应速度和测量的执行效率。     

固态功率组件热耦合效应研究

文中基于热叠加原理研究了固态功率组件中多个离散分布的集中热源的热耦合效应,并证明强迫对流下应用热叠加原理计算的温度场与整场系统数值模拟的结果相当吻合,用它来进行热耦合效应的分析研究是有效的.     

辐射换热的波长匹配问题

由于水的选择性吸收特性,辐射换热中水份波长匹配一直是一个有分歧的问题。文章通过理论与计算论证了这个问题,得出的结论否定了波长匹配的重要性。     

N-polar GaN基HEMT准二维电荷传输模型仿真

建立了氮极性(N-polar)GaN基HEMT器件的准二维(Quasi-2-D)电荷传输模型,仿真研究了N-polar GaN基HEMT的直流特性。仿真结果表明,不同的极化效应会对输出特性曲线和转移特性曲线产生不同的影响,考虑自发极化效应(Psp)+压电极化效应(Ppe)、只考虑Ppe和只考虑Psp三种情况下的阈值电压分别为:-3.96V、-2.29V和-2.47V,而其对应的峰值跨导则分别为44mS/mm、41.2mS/mm和41.3mS/mm。该模型为N-polar GaN基HEMT器件仿真提供了理论参考。     

Atomic Insights into Phase Evolution in Ternary Transition‐Metal Dichalcogenides Nanostructures

Phase engineering through chemical modification can significantly alter the properties of transition‐metal dichalcogenides, and allow the design of many novel electronic, photonic, and optoelectronics devices. The atomic‐scale mechanism underlying such phase engineering is still intensively investigated but elusive. Here, advanced electron microscopy, combined with density functional theory calculations, is used to understand the phase evolution (hexagonal 2H→monoclinic T′→orthorhombic T_d) in chemical vapor deposition grown Mo_{1− x} W _x Te₂ nanostructures. Atomic‐resolution imaging and electron diffraction indicate that Mo_{1− x} W _x Te₂ nanostructures have two phases: the pure monoclinic phase in low W‐concentrated (0 < x ≤ 10 at.%) samples, and the dual phase of the monoclinic and orthorhombic in high W‐concentrated (10 < x < 90 at.%) samples. Such phase coexistence exists with coherent interfaces, mediated by a newly uncovered orthorhombic phase T_d′. T_d′, preserves the centrosymmetry of T′ and provides the possible phase transition path for T′→T_d with low energy state. This work enriches the atomic‐scale understanding of phase evolution and coexistence in multinary compounds, and paves the way for device applications of new transition‐metal dichalcogenides phases and heterostructures.     

Direct numerical simulations for assessment of gas-solid drag models in two-dimensional random arrays of particles

The momentum exchange between the phases plays a vital role in modelling of gas–solid flows and it is mathematically described by drag models. However, no consensus exists on which drag model gives the most accurate prediction of the drag force, and, despite the increase in available computing power, the same drag models are used in two-dimensional and three-dimensional simulations. In this study, direct numerical simulations of gas flow through multiple random configurations of static monodisperse particles are performed. The variations of solid volume fraction and particle Reynolds number are in the ranges of 0.05–0.4 and 13.7–136.9, respectively. The drag force exerted on particles is calculated and properly averaged. Based on the simulation results, thirteen drag models are compared and correction factors are introduced using the stochastic gradient descent algorithm. The correction factors provide a simple adjustment for the models to be used in 2D modelling.     

Optimization of optical lens-controlled scanning electron microscopic resolution using generalized regression neural network and genetic algorithm

A scanning electron microscope (SEM) is a sophisticated equipment employed for fine imaging of a variety of surfaces. In this study, prediction models of SEM were constructed by using a generalized regression neural network (GRNN) and genetic algorithm (GA). The SEM components examined include condenser lens 1 and 2 and objective lens (coarse and fine) referred to as CL1, CL2, OL-Coarse, and OL-Fine. For a systematic modeling of SEM resolution (R), a face-centered Box–Wilson experiment was conducted. Two sets of data were collected with or without the adjustment of magnification. Root-mean-squared prediction error of optimized GRNN models are GA 0.481 and 1.96×10^-12 for non-adjusted and adjusted data, respectively. The optimized models demonstrated a much improved prediction over statistical regression models. The optimized models were used to optimize parameters particularly under best tuned SEM environment. For the variations in CL2 and OL-Coarse, the highest R could be achieved at all conditions except a larger CL2 either at smaller or larger OL-Coarse. For the variations in CL1 and CL2, the highest R was obtained at all conditions but larger CL2 and smaller CL1.     

On the generalized Hyers-Ulam stability of multi-quadratic mappings

A mapping f:Vⁿ?W, where V is a commutative group, W is a linear space, and n≥2 is an integer, is called multi-quadratic if it is quadratic in each variable. In this paper, we prove the generalized Hyers-Ulam stability of multi-quadratic mappings in Banach spaces and complete non-Archimedean spaces.     

Shape optimization for tumor location

In non-invasive thermal diagnostics, accurate correlations between the thermal image at skin surface and interior human physiology are desired. In this work, an estimation methodology to determine unknown geometrical parameters of an embedded tumor is proposed. We define a functional that represents the mismatch between a measured experimental temperature profile, which may be obtained by infrared thermography on the skin surface, and the solution of an appropriate boundary problem. This functional is related to the geometrical parameters through the solution of the boundary problem, in such a way that finding the minimum of this functional form also means finding the unknown geometrical parameters of the embedded tumor. Sensitivity analysis techniques coupled with the adjoint method were considered to compute the shape derivative of the functional. Then, a nonmonotone spectral projected gradient method was implemented to solve the optimization problem of finding the optimal geometric parameters.