Accurate spline solutions of the Dirac equation with parity-nonconserving potential

1/4波片quarter-wave plateCG矢量耦合系数Clebsch-Gordan vector coupling coefficient; 简称“CG[矢耦]系数”。

X射线摄谱仪X-ray spectrographX射线衍射X-ray diffractionX射线衍射仪X-ray diffractometer[玻耳兹曼]H定理[Boltzmann] H-theorem[玻耳兹曼]H函数[Boltzmann] H-function[彻]体力body force[冲]击波shock wave[冲]击波前shock front[狄拉克]δ函数[Dirac] δ-function[第二类]拉格朗日方程Lagrange equation[电]极化强度[electric] polarization[反射]镜mirror[光]谱线spectral line[光]谱仪spectrometer[光]照度illuminance[光学]测角计[optical] goniometer[核]同质异能素[nuclear] isomer[化学]平衡常量[chemical] equilibrium constant[基]元电荷elementary charge[激光]散斑speckle[吉布斯]相律[Gibbs] phase rule[可]变形体deformable body[克劳修斯-]克拉珀龙方程[Clausius-] Clapeyron equation[量子]态[quantum] state[麦克斯韦-]玻耳兹曼分布[Maxwell-]Boltzmann distribution[麦克斯韦-]玻耳兹曼统计法[Maxwell-]Boltzmann statistics[普适]气体常量[universal] gas constant[气]泡室bubble chamber[热]对流[heat] convection[热力学]过程[thermodynamic] process[热力学]力[thermodynamic] force[热力学]流[thermodynamic] flux[热力学]循环[thermodynamic] cycle[事件]间隔interval of events[微观粒子]全同性原理identity principle [of microparticles][物]态参量state parameter, state property[相]互作用interaction[相]互作用绘景interaction picture[相]互作用能interaction energy[旋光]糖量计saccharimeter[指]北极north pole, N pole[指]南极south pole, S pole[主]光轴[principal] optical axis[转动]瞬心instantaneous centre [of rotation][转动]瞬轴instantaneous axis [of rotation]t 分布student's t distributiont 检验student's t testＫ俘获K-captureＳ矩阵S-matrixＷＫＢ近似WKB approximationＸ射线X-rayΓ空间Γ-spaceα粒子α-particleα射线α-rayα衰变α-decayβ射线β-rayβ衰变β-decayγ矩阵γ-matrixγ射线γ-rayγ衰变γ-decayλ相变λ-transitionμ空间μ-spaceχ 分布chi square distributionχ 检验chi square test阿贝不变量Abbe invariant阿贝成象原理Abbe principle of image formation阿贝折射计Abbe refractometer阿贝正弦条件Abbe sine condition阿伏伽德罗常量Avogadro constant阿伏伽德罗定律Avogadro law阿基米德原理Archimedes principle阿特伍德机Atwood machine艾里斑Airy disk爱因斯坦-斯莫卢霍夫斯基理论Einstein-Smoluchowski theory 爱因斯坦场方程Einstein field equation爱因斯坦等效原理Einstein equivalence principle爱因斯坦关系Einstein relation爱因斯坦求和约定Einstein summation convention爱因斯坦同步Einstein synchronization爱因斯坦系数Einstein coefficient安[培]匝数ampere-turns安培[分子电流]假说Ampere hypothesis安培定律Ampere law安培环路定理Ampere circuital theorem安培计ammeter安培力Ampere force安培天平Ampere balance昂萨格倒易关系Onsager reciprocal relation凹面光栅concave grating凹面镜concave mirror凹透镜concave lens奥温电桥Owen bridge巴比涅补偿器Babinet compensator巴耳末系Balmer series白光white light摆pendulum板极plate伴线satellite line半波片halfwave plate半波损失half-wave loss半波天线half-wave antenna半导体semiconductor半导体激光器semiconductor laser半衰期half life period半透[明]膜semi-transparent film半影penumbra半周期带half-period zone傍轴近似paraxial approximation傍轴区paraxial region傍轴条件paraxial condition薄膜干涉film interference薄膜光学film optics薄透镜thin lens保守力conservative force保守系conservative system饱和saturation饱和磁化强度saturation magnetization本底background本体瞬心迹polhode本影umbra本征函数eigenfunction本征频率eigenfrequency本征矢[量] eigenvector本征振荡eigen oscillation本征振动eigenvibration本征值eigenvalue本征值方程eigenvalue equation比长仪comparator比荷specific charge; 又称“荷质比(charge-mass ratio)”。

章节内容概述
• 第7章-续 – 例题 6 - 低压气轮机箱的热分析
• 第 8 章 - 辐射 – 辐射概念的回顾 – 基本定义 – 辐射建模的可选择方法 – 辐射矩阵模块 – 辐射分析例题 - 使用辐射矩阵模块进行热沉分析，隐式和非隐式方 法。
• 第 9 章 - 相变 – 基本模型/术语 – 在 ANSYS中求解相变 – 相变例题 - 飞轮铸造分析
传导
• 传导的热流由传导的傅立叶定律决定：
q*
=
− Knn
∂T ∂n
=
heat
flow
rate
per
unit
area
in
direction
n
Where, Knn = thermal conductivity in direction n
T = temperature
∂T = thermal gradient in direction n ∂n
• 负号表示热沿梯度的反向流动(i.e., 热从热的部分流向冷的).
q*
T
dT
dn
n
对流
• 对流的热流由冷却的牛顿准则得出:
q* = hf (TS − TB ) = heat flow rate per unit area between surface and fluid
Where, hf = convective film coefficient TS = surface temperature TB = bulk fluid temperature
• 第 6 章 - 复杂的, 时间和空间变化的边界条件 – 表格化的热边界条件 (载荷) – 基本变量 – 用户定义的因变变量
章节内容概述

reaching out into the unburnt gas somehow propagate slower than do concave regions which are hot gases surrounding a small unburnt pocket. At the same time, particles along the flame front undergo an increase in volume as they burn, creating a jump in velocity across the flame front. This discontinuity in the velocity field creates vorticity along the burning flame, which can be related to the local curvature, and this new vorticity field contributes to the advection of the propagating flame. Thus, there are at least two distinct ways in which the speed of the moving flame depends on the local curvature. Typically, there have been two types of numerical algorithms employed in the solution of such problems. The first parameterizes the moving front by some variable and discretizes this parameterization into a set of marker points [39]. The positions of the marker points are updated in time according to approximations to the equations of motion. Such techniques can be extremely accurate in the attempt to follow the motions of small perturbations. However, for large, complex motion, several problems soon occur. First, marker particles come together in regions where the curvature of the propagating front builds, causing numerical instability unless a regridding technique is employed. The regridding mechanism usually contains a error term which resembles diffusion and dominates the real effects of curvature under analysis. Secondly, such methods suffer from topological problems; when two regions "burn" together to form a single one, ad-hoc techniques to eliminate parts of the boundary are required to make the algorithm work. Other algorithms commonly employed fall under the category of "volume of fluid " techniques, which, rather than track the boundary of the propagating front, track the motion of the interior region. An example of this type of algorithm is SLIC [26]. In these algorithms, the interior is discretized, usually by employing a grid on the domain and assigning to each cell a "volume fraction" corresponding to the amount of interior fluid currently located in that cell. An advantage of such techniques is that no new computational elements are required as the calculation progresses (unlike the parameterization methods), and complicated topological boundaries are easily handled, see [4,32]. Unfortunately, it is difficult to calculate the curvature of the front from such a representa-

Jeremy C. Hebden Department of Medical Physics and Bioengineering, University College London, 11-20 Capper Street,
London WC1E 6JA, UK
Simon R. Arridge Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK
OCIS codes: 170.5280, 290.7050, 290.1990.
1. INTRODUCTION
Optical tomography (OT) deals with the problem of retrieving spatial functions of internal physical properties of a body from a set of optical measurements.1 Examples of such functions are scattering and absorption coefficients (in biomedical applications) or the refractive index (in plasma physics research). Since biological tissues are relatively low absorbing in the optical window ranging from ␭ ϭ 700 nm to ␭ ϭ 1000 nm, most medical applications of OT are carried out in that range. Unfortunately, most biological tissues also strongly scatter light, which represents a serious problem for viewing the body’s internal structures and characterizing biological processes by optical methods.2–4