Gradient second order

Normally, the extra stress in the equation of motion is substituted in terms of velocity gradients and hence this equation includes second order derivatives of... 

Because the Navier-Stokes equations are first-order in pressure and second-order in velocity, their solution requires one pressure bound-aiy condition and two velocity boundaiy conditions (for each velocity component) to completely specify the solution. The no sBp condition, whicn requires that the fluid velocity equal the velocity or any bounding solid surface, occurs in most problems. Specification of velocity is a type of boundary condition sometimes called a Dirichlet condition. Often boundary conditions involve stresses, and thus velocity gradients, rather than the velocities themselves. Specification of velocity derivatives is a Neumann boundary condition. For example, at the boundary between a viscous liquid and a gas, it is often assumed that the liquid shear stresses are zero. In numerical solution of the Navier-... 

MoUer-Plesset perturbation theory energies through fifth-order (accessed via the keywords MP2, MP3, MP4, and MP5), optimizations via analytic gradients for second-order (MP2), third-order (MP3) and fourth-order (without triples MP4SDQ), and analytic frequencies for second-order (MP2). 

Requiring the gradient of the second-order approximation (14.3) to be zero produces the... 

The advantage of the NR method is that the convergence is second-order near a stationary point. If the function only contains tenns up to second-order, the NR step will go to the stationary point in only one iteration. In general the function contains higher-order terms, but the second-order approximation becomes better and better as the stationary point is approached. Sufficiently close to tire stationary point, the gradient is reduced quadratically. This means tlrat if the gradient norm is reduced by a factor of 10 between two iterations, it will go down by a factor of 100 in the next iteration, and a factor of 10 000 in the next ... 

The above second-order differential equation can be solved by integration. At the liquid surface, where Z=0, the bulk gas concentration, Cso. is known, but the concentration gradient dCs/dZ is unknown. Conversely at the full liquid depth, the concentration Cso is not known, but the concentration gradient is known and is equal to zero. Since there can be no diffusion of component S from the bottom surface of the liquid, i.e., js at Z=L is 0 and hence from Pick s Law dCs/dZ at Z=L must also be zero. 

Schmider, H. L., Becke, A. D., 1998b, Density Functionals from the Extended G2 Test Set Second-Order Gradient Corrections , J. Chem. Phys., 109, 8188. 

If the two competing reactions have the same concentration dependence, then the catalyst pore structure does not influence the selectivity because at each point within the pore structure the two reactions will proceed at the same relative rate, independent of the reactant concentration. However, if the two competing reactions differ in the concentration dependence of their rate expressions, the pore structure may have a significant effect on the product distribution. For example, if V is formed by a first-order reaction and IF by a second-order reaction, the observed yield of V will increase as the catalyst effectiveness factor decreases. At low effectiveness factors there will be a significant gradient in the reactant concentration as one moves radially inward. The lower reactant concentration within the pore structure would then... 

Figure 13 Timing diagram for the clean HMBC experiment with an initial second-order and terminal adiabatic low-pass 7-filter.42,43 The recommended delays for the filters are the same than for a third-order low-pass J filter. <5 and 8 are gradient delays, where 8 — <5 + accounts for the delay of the first point in the 13C dimension. The integral over each gradient pulse G, is H/2yc times the integral over gradient G2 in order to achieve coherence selection. The recommended phase cycle is c/)n = x, x, x, x 3 — 4(x), 4(y), 4( x), 4(—y) with the receiver phase c/)REC = x, x.

Instead of a formal development of conditions that define a local optimum, we present a more intuitive kinematic illustration. Consider the contour plot of the objective function fix), given in Fig. 3-54, as a smooth valley in space of the variables X and x2. For the contour plot of this unconstrained problem Min/(x), consider a ball rolling in this valley to the lowest point offix), denoted by x. This point is at least a local minimum and is defined by a point with a zero gradient and at least nonnegative curvature in all (nonzero) directions p. We use the first-derivative (gradient) vector Vf(x) and second-derivative (Hessian) matrix V /(x) to state the necessary first- and second-order conditions for unconstrained optimality ... 

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