Dimensional instability

The smectic A phase is a liquid in two dimensions, i.e. in tire layer planes, but behaves elastically as a solid in the remaining direction. However, tme long-range order in tliis one-dimensional solid is suppressed by logaritlimic growth of tliennal layer fluctuations, an effect known as tire Landau-Peierls instability [H, 12 and 13]... 

Laminar flame instabilities are dominated by diffusional effects that can only be of importance in flows with a low turbulence intensity, where molecular transport is of the same order of magnitude as turbulent transport (28). Flame instabilities do not appear to be capable of generating turbulence. They result in the growth of certain disturbances, leading to orderly three-dimensional stmctures which, though complex, are steady (1,2,8,9). 

Many coating flows are subject to instabilities that lead to unacceptable coating defects. Three-dimensional flow instabilities lead to such problems as ribbing. Air entrainment is another common defect. 

Dimensional instability due to a high temperature coefficient of expansion and a high water absorption. 

Fig. 6.7. The predicted, one-dimensional, mean-bulk temperatures versus location at various times are shown for a typical powder compact subjected to the same loading as in Fig. 6.5. It should be observed that the early, low pressure causes the largest increase in temperature due to the crush-up of the powder to densities approaching solid density. The "spike in the temperature shown on the profiles at the interfaces of the powder and copper is an artifact due to numerical instabilities (after Graham [87G03]).

Minols are gray in color, have densities ranging between 1.62 and 1.74g/cc, and are cast loaded. They resemble Torpex in explosive properties, but are less brisant. They exhibit dimensional instability when exposed to thermal cycling during long term storage... 

This occurs, for instance, when a molded manufact tends to have a transition between polymorphic forms in conditions of use. In fact solid-solid transitions can generate problems of dimensional instability of the manufacts. 

Peles el al. (2000) elaborated on a quasi-one-dimensional model of two-phase laminar flow in a heated capillary slot due to liquid evaporation from the meniscus. Subsequently this model was used for analysis of steady and unsteady flow in heated micro-channels (Peles et al. 2001 Yarin et al. 2002), as well as the study of the onset of flow instability in heated capillary flow (Hetsroni et al. 2004). 

The quasi-one-dimensional model allows analyzing the behavior of the vapor-liquid system, which undergoes small perturbations. In the frame of the linear approximation the effect of physical properties of both phases, the wall heat flux and the capillary sizes, on the flow instability is studied, and a scenario of the development of a possible processes at small and moderate Peclet number is considered. 

It is worth mentioning here several things for later use. Scheme (33) with the boundary conditions (45) is in common usage for step-shaped regions G, whose sides are parallel to the coordinate axes. In the case of an arbitrary domain this scheme is of accuracy 0( /ip + r Vh). Scheme (9)-(10) cannot be formally generalized for the three-dimensional case, since the instability is revealed in the resulting scheme. 

P. Clavin, P. Pelc and L. He. One-dimensional vibratory instability of planar flames propagating in tubes. Journal of Fluid Mechanics, 216 299-322, 1990. 

A difiiculty with this mechanism is the small nucleation rate predicted (1). Surfaces of a crystal with low vapor pressure have very few clusters and two-dimensional nucleation is almost impossible. Indeed, dislocation-free crystals can often remain in a metastable equilibrium with a supersaturated vapor for long periods of time. Nucleation can be induced by resorting to a vapor with a very large supersaturation, but this often has undesirable side effects. Instabilities in the interface shape result in a degradation of the quality and uniformity of crystalline material. 

This equation has been derived as a model amplitude equation in several contexts, from the flow of thin fluid films down an inclined plane to the development of instabilities on flame fronts and pattern formation in reaction-diffusion systems we will not discuss here the validity of the K-S as a model of the above physicochemical processes (see (5) and references therein). Extensive theoretical and numerical work on several versions of the K-S has been performed by many researchers (2). One of the main reasons is the rich patterns of dynamic behavior and transitions that this model exhibits even in one spatial dimension. This makes it a testing ground for methods and algorithms for the study and analysis of complex dynamics. Another reason is the recent theory of Inertial Manifolds, through which it can be shown that the K-S is strictly equivalent to a low dimensional dynamical system (a set of Ordinary Differentia Equations) (6). The dimension of this set of course varies as the parameter a varies. This implies that the various bifurcations of the solutions of the K-S as well as the chaotic dynamics associated with them can be predicted by low-dimensional sets of ODEs. It is interesting that the Inertial Manifold Theory provides an algorithmic approach for the construction of this set of ODEs. 

Thermally driven convective instabilities in fluid flow, and, more specifically, Rayleigh-B6nard instabilities are favorite working examples in the area of low-dimensional dynamics of distributed systems (see (14 and references therein). By appropriately choosing the cell dimensions (aspect ratio) we can either drive the system to temporal chaos while keeping it spatially coherent, or, alternatively, produce complex spatial patterns. 

The presentation in this paper concentrates on the use of large-scale numerical simulation in unraveling these questions for models of two-dimensional directional solidification in an imposed temperature gradient. The simplest models for transport and interfacial physics in these processes are presented in Section 2 along with a summary of the analytical results for the onset of the cellular instability. The finite-element analyses used in the numerical calculations are described in Section 3. Steady-state and time-dependent results for shallow cell near the onset of the instability are presented in Section 4. The issue of the presence of a fundamental mechanism for wavelength selection for deep cells is discussed in Section 5 in the context of calculations with varying spatial wavelength. 

The transition from WA( ) = 1 to WA( ) = 0 as the distance from the nucleus A increases needs to be smooth enough such that numerical instabilities are avoided but at the same time also as abrupt as possible such that density peaks from nearby the nuclei are extinguished. The implementation of this concept in the three-dimensional space involves a special choice of coordinates - see Becke, 1988c, for details - but actually leads to a smoothened step function as schematically sketched in Figure 7-1 for the one-dimensional case. 

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