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Simulations of Microstructure

The process of making samples, visualizing the microstructure and measuring the physical and sensory properties is expensive and [Pg.116]


R. G. Larson. Monte Carlo simulations of microstructural transitions in surfactant systems. J Chem Phys 96 7904-7918, 1992. [Pg.742]

T. Hoshide. Simulation of microstructural effects on cracking behavior in biaxial fatigue. Mater Sci Res Int 5 119, 1997. [Pg.929]

Y. Saito. The Monte Carlo simulation of microstructural evolution in metals. Mater Sci and Eng A 99 114, 1997. [Pg.930]

S. Johnston et al Three-dimensional finite element simulations of microstructurally small fatigue crack growth in 7,075 aluminium alloy. Fatigue Fract. Eng. Matl. Struct. 29,597-605 (2006)... [Pg.129]

FIGURE 27.7 Computer simulations of microstructures of (a-d) PZT and (e-h) SrTiOs thin-film cross sections illustrating microstructural evolution at various times during the transformation to the perovskite state. Lighter colors associated with intermediate phase darker colors associated with the perovskite phase. [Pg.550]

H.M Jennings and S.K Johnson, Simulation of microstructure development during the hydration... [Pg.55]

A. Vishnyakov and A. V. Neimark, Molecular Dynamics Simulation of Microstructure and Molecular Mobilities in Swollen Nafion Membranes, Journal of Physical Chemistry B, 105, 9586 (2001). [Pg.195]

In addition, the models can be used for generating virtual materials, that is, they can generate microstructures of GDIs which have not been recorded so far. The combination of stochastic simulation of microstructures and numerical simulation of functionality leads to the concept of the so-called virtual material design, that is, the investigation and/or optimization of GDL morphologies based on computer experiments. This approach can be a valuable extension to physical experiments since computer experiments can be executed fairly fast and cheaply. Hence, many more scenarios than with physical experiments can be generated and analyzed in detail. [Pg.699]

Vishnyakov A, Neimark AV. Moleenlar dynamies simulation of microstructure and molecular mobilities in swollen Nation membranes. J Phys Chem B 2001 105(39) 9586-94. [Pg.444]

Simulation of microstructural evolution of single-phase ceramic tool material... [Pg.159]

Vishnyakov, A. and Neimark, A. V. 2001. Molecular dynamics simulation of microstructure and molecular mohihties in swollen Nafion membranes. 105(39), 9586-... [Pg.508]

A special mention is in order of high-resolution electron microscopy (HREM), a variant that permits columns of atoms normal to the specimen surface to be imaged the resolution is better than an atomic diameter, but the nature of the image is not safely interpretable without the use of computer simulation of images to check whether the assumed interpretation matches what is actually seen. Solid-state chemists studying complex, non-stoichiometric oxides found this image simulation approach essential for their work. The technique has proved immensely powerful, especially with respect to the many types of defect that are found in microstructures. [Pg.221]

Baskes (1999) has discussed the status role of this kind of modelling and simulation, citing many very recent studies. He concludes that modelling and simulation of materials at the atomistic, microstructural and continuum levels continue to show progress, but prediction of mechanical properties of engineering materials is still a vision of the future . Simulation cannot (yet) do everything, in spite of the optimistic claims of some of its proponents. [Pg.481]

T. Hoshide, K. Kusuura. Life prediction by simulation of crack growth in notched components with different microstructures and under multiaxial fatigue. Fatigue Fract Eng Mater Struct 27 201, 1998. [Pg.926]

H. Li, F. Czerwinski, J. A. Szpunar. Monte-Carlo simulation of texture and microstructure development in nanocrystalhne electrodeposits. Nanostruct Mater 9 673, 1997. [Pg.930]

To examine replication of IPBs we made MFKEi-based simulations using the simplest 2D alloy model with the nearest-neighbor interaction. Some results are presented in Figs. 8-10. The lower row in Fig. 10 illustrates possible effects of thermal fluctuations, similar to those discussed in Sec. 3 for the replication of APBs. The figure shows that peculiar features of microstructural evolution are preserved even under rather strong thermal fluctuations used in this simulation. [Pg.108]

The simulations of fluid flow and heat transfer in such microstructured geometries were carried out with an FVM solver. Air with an inlet temperature of 100 °C was considered as a fluid, and the channel walls were modeled as isothermal with a temperature of 0 °C. The streamline pattern is characterized by recirculation zones which develop behind the fins at comparatively high Reynolds numbers. The results of the heat transfer simulations are summarized in Figure 2.34, which shows the Nusselt number as a fimction of Reynolds number. For... [Pg.192]

Molecular calculations provide approaches to supramolecular structure and to the dynamics of self-assembly by extending atomic-molecular physics. Alternatively, the tools of finite element analysis can be used to approach the simulation of self-assembled film properties. The voxel4 size in finite element analysis needs be small compared to significant variation in structure-property relationships for self-assembled structures, this implies use of voxels of nanometer dimensions. However, the continuum constitutive relationships utilized for macroscopic-system calculations will be difficult to extend at this scale because nanostructure properties are expected to differ from microstructural properties. In addition, in structures with a high density of boundaries (such as thin multilayer films), poorly understood boundary conditions may contribute to inaccuracies. [Pg.144]

Figure 2.16. (a-c) Simulations of film structural evolution for PZT thin films at various times during heat treatment.15 (d) A representative SEM photomicrograph illustrating the columnar microstructure of PZT.48 The lower layer is the lower Pt electrode, the middle layer is the PZT, and the upper layer is the top Pt electrode, [(a)-(c) Reprinted with permission from Ref. 15. (d) Reprinted with permission from Ref. 9. Copyright 1997 American Chemical Society.] (See color insert.)... [Pg.67]

Figure 36. Cathode voltage loss as predicted by direct numerical simulation of proton, oxygen, and water transport in a catalyst layer at the pore level (left), and three-dimensional oxygen concentration contours in a random microstructure of the catalyst layer (right). Figure 36. Cathode voltage loss as predicted by direct numerical simulation of proton, oxygen, and water transport in a catalyst layer at the pore level (left), and three-dimensional oxygen concentration contours in a random microstructure of the catalyst layer (right).
Current research efforts are concentrating on computationally efficient implementations of the energy equation within the MicroFlowS framework to allow realistic simulations of soot particle reaction in the porous structures. The next section shows a parallel line of development that started in Konstandopoulos and Kostoglou (2004), which tries to extend continuum models of soot oxidation to account for microstructural effects. [Pg.234]

The phase-field simulations reproduce a wide range of microstructural phenomena such as dendrite formation in supercooled fixed-stoichiometry systems [10], dendrite formation and segregation patterns in constitutionally supercooled alloy systems [11], elastic interactions between precipitates [12], and polycrystalline solidification, impingement, and grain growth [6]. [Pg.441]

The aforementioned numerical experiments, namely quasi-static drainage and steady-state flow simulations, are specifically designed to study the influence of microstructure and wetting characteristics on the underlying two-phase behavior and flooding dynamics in the PEFC CL and GDL. [Pg.277]

Abstract We present a method for simulation of collagen gels and more generally for materials comprised of a fibrillar network. The method solves a representative microstructural problem on each finite element in lieu of a constitutive equation. The method captures key features of microstructural rearrangement while maintaining the ability to perform simulations on the (large) functional length scale. [Pg.41]

The constitutive equations use a thermodynamic framework, that in fact embodies not only purely mechanical aspects, but also transfers of masses between the phases and diffusion of matter through the extrafibrillar phase. Since focus is on the chemo-mechanical couplings, we use experimental data that display different salinities. The structure of the constitutive functions and the state variables on which they depend are briefly motivated. Calibration of material parameters is defined and simulations of confined compression tests and of tree swelling tests with a varying chemistry are described and compared with available data in [3], The evolution of internal entities entering the model, e.g. the masses and molar fractions of water and ions, during some of these tests is also documented to highlight the main microstructural features of the model. [Pg.168]


See other pages where Simulations of Microstructure is mentioned: [Pg.116]    [Pg.378]    [Pg.79]    [Pg.159]    [Pg.167]    [Pg.116]    [Pg.378]    [Pg.79]    [Pg.159]    [Pg.167]    [Pg.930]    [Pg.9]    [Pg.11]    [Pg.3]    [Pg.182]    [Pg.159]    [Pg.355]    [Pg.67]    [Pg.170]    [Pg.233]    [Pg.365]    [Pg.513]    [Pg.524]    [Pg.265]    [Pg.49]    [Pg.97]    [Pg.99]   


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