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Composite modeling

Fig. 11 shows a composite model of the wave at U X =0.25. In the interfering wave on the upper and lower part of the insert metal, (a) is the same phase, and (b) is the opposite phase. A composite wave is attenuated by the weakened interference as the same phase, and is amplified by the strengthened interference as the opposite phase. [Pg.838]

Mechanical Properties. Although wool has a compHcated hierarchical stmcture (see Fig. 1), the mechanical properties of the fiber are largely understood in terms of a two-phase composite model (27—29). In these models, water-impenetrable crystalline regions (generally associated with the intermediate filaments) oriented parallel to the fiber axis are embedded in a water-sensitive matrix to form a semicrystalline biopolymer. The parallel arrangement of these filaments produces a fiber that is highly anisotropic. Whereas the longitudinal modulus of the fiber decreases by a factor of 3 from dry to wet, the torsional modulus, a measure of the matrix stiffness, decreases by a factor of 10 (30). [Pg.342]

The local-composition models have hmited flexibility in the fitting of data, but they are adequate for most engineering purposes. Moreover, they are implicitly generalizable to multicomponent systems without the introduction of any parameters beyond those required to describe the constituent binaiy systems. For example, the Wilson equation for multicomponent systems is written ... [Pg.533]

The above qualitative conclusions made on the basis of the results of [116, 124-127] correlate with the results of [129,130] in which the calculation is based on composite models with nucleus-shell inclusions. The authors illustrate this with the calculation of a system consisting of a hard nucleus and elastomeric shell in a matrix of intermediate properties, and a system where the nucleus and matrix properties are identical whereas the shell is much more rigid. The method may, however, be also applied to systems with inclusions where the nucleus is enclosed in a multi layer shell. Another, rather unexpected, result follows from [129,130] for a fixed inclusions concentration, the relative modulus of the system decreases with increasing nucleus radius/inclusion radius ratio, that is with decreasing shell thickness. [Pg.16]

Smith et al.511 have recently suggested a composite model based on similar considerations to predict k over the entire chain length range. Experimental data for k A for dodecyl methacrylate polymerization consistent with such a model have been provided by Buback et rd. J... [Pg.247]

Recently, Teymour and coworkers developed an interesting computational technique called the digital encoding for copolymerization compositional modeling [20,21], Their method uses symbolic binary arithmetic to represent the architecture of a copolymer chain. Here, each binary number describes the exact monomer sequence on a specific polymer chain, and its decimal equivalent is a unique identifier for this chain. Teymour et al. claim that the... [Pg.110]

Example applies the composite model of bonding to the acetate anion. [Pg.709]

The acetate anion (CH3 CO2 ) forms when acetic acid, the acid present in vinegar, is treated with hydroxide ion CH3 CO2 H -1- OH" -> CH3 CO2 + H2 O Use the four guidelines of the composite model of bonding to describe the bonding of this anion. Sketch the a bonding system and the occupied 7t... [Pg.709]

Follow the four-step procedure for the composite model of bonding. Use localized bonds and hybrid orbitals to describe the bonding framework and the inner atom lone pairs. Next, analyze the system, paying particular attention to resonance structures or conjugated double bonds. Finally, make sure the bonding inventory accounts for all the valence electrons and all the valence orbitals. [Pg.715]

Au-Ni and Cu-Ni-Au alloys Magnetic hyperfine spitting at Au, // and isomer shift as function of composition, model to describe charge density distribution... [Pg.371]

Although the use of this model considerably simplifies the quantitative analysis of data, it implicitly assumes that phase 2 is maintained at a constant composition during a measurement. Henceforth, we refer to the model described by Eqs. (l)-(5) as the constant-composition model. [Pg.298]

The numerical model developed to treat this problem [49], involves the parameters K, y, and the normalized tip-interface distance, L = d/a. To develop an understanding of the factors governing the SECM feedback response, which is of importance in the interpretation of experimental data, we briefly describe the effect of these parameters on the tip current. A key aim is to define precisely the conditions under which the simpler constant-composition model Eqs. (l)-(5) can be used. [Pg.300]

The effect on the normalized approach curves of allowing to take finite values is illustrated in Fig. 5, which shows simulated data for three rate constants, for redox couples characterized by y = 1. The rate parameters considered K = 100 (A), 10 (B), and 1 (C), are typical of the upper, medium, and lower constants that might be encountered in feedback measurements at liquid-liquid interfaces. In each case, values of = 1000 or 100 yield approach curves which are identical to the constant-composition model [44,47,48]. This behavior is expected, since the relatively high concentration of Red2 compared to Red] ensures that the concentration of Red2 adjacent to the liquid-liquid interface is maintained close to the bulk solution value, even when the interfacial redox process is driven at a fast rate. [Pg.300]

The reasons for the deviation of the constant-composition model from the full model are apparent when the concentrations of Red] and Red2 are examined. Due to the axi-symmetrical SECM geometry, the eoncentration profiles of Red] and Red2 are best shown as cross-sections over the domain / > 0, Z > 0, as illustrated sehematically in Fig. 6. Note that in this figure the tip position has been inverted eompared to that in Fig. 4. Figure 7... [Pg.301]

Although there are differences in the approach curves with the constant-composition model, it would be extremely difficult to distinguish between any of the K cases practically, unless K was below 10. Even for K = 10, an uncertainty in the tip position from the interface of 0. d/a would not allow the experimental behavior for this rate constant to be distinguished from the diffusion-controlled case. For a typical value of Z)Red, = 10 cm s and electrode radius, a= 12.5/rm, this corresponds to an effective first-order heterogeneous rate constant of just 0.08 cm s. Assuming K,. > 20 is necessary... [Pg.303]

FIG. 8 Contour plot of percentage error in the rate constant that results from analyzing data in terms of the constant-composition model, rather than the full diffusion model. The data are for a tip-ITIES separation, d/a = 0.1, with a range of K and values. (Reprinted from Ref. 49. Copyright 1999 American Chemical Society.)... [Pg.304]

In initial ET rate measurements, both the NB and aqueous phases contained 0.1 M TEAP, enabling measurements to be made with a constant Galvani potential difference across the liquid junction. In these early studies, the concentration of Fc used in the organic phase (phase 2) was at least 50 times the concentration of the electroactive mediator in the aqueous phase which contained the probe UME (phase 1). This ensured that the interfacial process was not limited by mass transport in the organic phase, and that the simple constant-composition model, described briefly in Section IV, could be used. [Pg.314]

For the transformation of the macrocomposite model to a molecular composite model for the ultimate strength of the fibre the following assumptions are made (1) the rods in the macrocomposite are replaced by the parallel-oriented polymer chains or by larger entities like bundles of chains forming fibrils and (2) the function of the matrix in the composite, in particular the rod-matrix interface, is taken over by the intermolecular bonds between the chains or fibrils. In order to evaluate the effect of the chain length distribution on the ultimate strength the monodisperse distribution, the Flory distribution, the half-Gauss and the uniform distribution are considered. [Pg.55]

A high mechanical anisotropy is characterised by a small value of jlz. Application of the composite model to a fibre implies that Vc=l. For very long chains or b—>°o Eq. 45 is derived... [Pg.64]

The composite model is a combination of the monoparametric v model with the simple branching model. This method has proven useful in modelling amino acid, peptide and protein properties49. It is an improvement over the simple branching model and requires only one additional parameter. [Pg.710]

Bishop, R. L., Aspects of Ceramic Compositional Modeling, In Models and Methods in Regional Exchange, SAA Papers No. 1, pp. 47-66, Society for American Archaeology, Washington, 1980. [Pg.435]

A simple composite model of slow motions and molecular reorientations is the so-called slowly relaxing local structure model by Freed.156,157 This... [Pg.105]


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Aerosol receptor models, composition

Alloy composition kinetic model

Aluminum compositional model

Binary Copolymer Composition - Terminal Model

Biodegradation modelling composite materials made

Boyd composite model

Carbon core compositional model

Central composite designs with response surface models

Chemical Bonding in Cyclic-cluster Model Local Properties of Composite Crystalline Oxides

Chemical vapor deposition, modeling composition

Complex permittivity composite model

Composite Nielsen model

Composite crash modelling

Composite delamination models

Composite finite element model

Composite materials biodegradation modelling

Composite materials modelling with defects

Composite materials, modeling

Composite model

Composite model, Takayanagi

Composite models, liquid water

Composite networks models

Composite plating models

Composite polymer electrolytes model

Composite sphere model

Composite stress models

Composite structure models

Composites aramid/epoxy model

Composites crystalline bridge model

Composites simple model

Composition gradient model

Composition model, local

Composition model, local application

Composition model, local development

Composition profiles in the synthesis of MTBE obtained by a multilevel modeling approach

Compositional analysis alternative models

Compositional data, modeling

Compositional data, modeling summarizing

Constant-composition model

Core-mantle composite model

Fiber Composite Model

Finite element textile composites modelling

Gold core compositional model

Heavy water composite model

Hydrogen core compositional model

Ionic polymer-metal composite models

Ionic polymer-metal composites actuation model

Ionic polymer-metal composites electromechanical modeling

Iron core compositional model

Lead core compositional model

Local composition model activity coefficient prediction

Magnesium compositional model

Manganese compositional model

Mathematical Model with Actual Conventional and Modified Composite Boards

Metal matrix composites models

Model complete local-composition equation

Model-generated pressure-composition

Modeling of Composite Electrodes

Modeling of crystallization in fiber-reinforced composites

Modeling the dust composition

Modelling dynamic changes in headspace gas composition

Models alloy surface composition

Morphological Developments of the Composite Model

Multiple fiber composite model

Nickel compositional model

Oxygen core compositional model

PEFC model composition

Phenomenological Model for Compositional Ripening

Polymer composites models

Polymer matrix composites model

Polymeric Membrane Models composition

Polymeric composites coupling model

Potential wells composite model

Predicted results of the composite model and comparison with experiments

Retention Modeling as Function of Mobile Phase Composition

Self-consistent wells composite model

Silicon core compositional model

Single fiber composite model

Sodium compositional model

Source models, composition

Steric effects composite model

Structural equation modeling composite

Sulfur core compositional model

Testing and modeling the mechanical behavior of nanofibers for composite applications

The Keiretsu Will Follow a Composite Supply Chain Model

Theoretical models, nanotube composites

Three-cylinder composite model

Titanium compositional model

Wetting models composite interface

Woven composites failure modelling

Woven composites stiffness modelling

Woven composites stress modelling

Woven composites textile composite models

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