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Correlations between

For the acetone-methanol data of Othmer, the correlation coefficient is -0.678, indicating a moderate degree of correlation between the two van Laar parameters. The elongated confidence ellipses shown in Figure 2 further emphasize this correlation. [Pg.104]

Hammen equation A correlation between the structure and reactivity in the side chain derivatives of aromatic compounds. Its derivation follows from many comparisons between rate constants for various reactions and the equilibrium constants for other reactions, or other functions of molecules which can be measured (e g. the i.r. carbonyl group stretching frequency). For example the dissociation constants of a series of para substituted (O2N —, MeO —, Cl —, etc.) benzoic acids correlate with the rate constant k for the alkaline hydrolysis of para substituted benzyl chlorides. If log Kq is plotted against log k, the data fall on a straight line. Similar results are obtained for meta substituted derivatives but not for orthosubstituted derivatives. [Pg.199]

A correlation between retention times and boiling points is established by calibration with a known mixture of hydrocarbons, usually normal paraffins, whose boiling points are known (see Figure 2.2). From this information, the distribution of boiling points of the sample mixture is obtained. [Pg.21]

An example of the good correlation between TBP and simulated distillation is given in Figure 2.4, where it is shown that 71% of a Kuwait crude distils below 535T. [Pg.24]

Other correlations between NMR and infrared have been studied because the latter technique is less cui ersonje than NMR. Correlations are obtained not just on the two absorption bands but on the whole of the IR spectrum after reduction of the spectrum into its principal components. [Pg.62]

There also exist relatively simple correlations between the heating value of motor fuels and certain characteristics such as density and composition by chemical family supplied by FIA analysis. Refer to Chapter 3. [Pg.181]

The volatility of the fuel is expressed then by the temperature levels for which the V/L ratio is equal to certain particular values for example V/L = 12, V/L = 20, V/L = 36. There are correlations between the temperatures corresponding to these vaporization ratios and the conventional volatility parameters such as the RVP and the distillation curve. [Pg.192]

Cetane index ASTM D 4737 ISO 4264 Correlation between density and distillation... [Pg.446]

Typical correlation between noise and stress in uniaxial stress state... [Pg.4]

Typical correlation between the magnetic characteristic and the body force measured on the head of 85 mm long M24 Friedberg 10.9 bolts where the thickness off the plates screwed together is more than 40mm. [Pg.6]

Correlation between the forces in the body of the bolt and the stress state in the head of the bolt... [Pg.7]

Correlation between the body forces and the stress state in the head was investigated both by the strain gauge method and the optical coat work stress examination method, and the magnetic measurements were performed at the same time. [Pg.7]

The last part, following the method to analyse radioscopy and acoustic emission values, will be to correlate the characteristic values of the radioscopic detection of casting defects with extracted characteristic values of the acoustic emission analysis. The correlation between the time based characteristic values of acoustic emission analysis and the defect characterizing radioscopy values did not come to very satisfactory results referring the low frequency measurements. The reason can be found in the... [Pg.16]

The results of over 1 year of continuous, on-line acoustic emission (AE) structural surveillance of high temperature / high pressure steam headers, gained on 2 M-scale 600MW supercritical multifuel ENEL power units in normal operation, are presented in the paper. The influence of background noise, the correlation between plant operating conditions (steady load, load variations, startup / shutdown transients) and AE activity and the diagnostic evaluation of recorded AE events are also discussed. [Pg.75]

Different plant operating conditions (steady load, load variations, startups / shutdowns) have been encountered during the monitoring period. Electrical load, steam pressure and steam temperature values vs time have been acquired and stored during the entire period. At the same time, the RMS values of the acoustical background noise were have been continuously checked and stored, thus providing a quick check of proper instrumentation condition and a correlation between variations of plant parameters and the acoustical behaviour of the components. [Pg.78]

Representative set of weldments was examined site welds (with pearlitic type weld metal) and two types of site weld repair zones with different welding technologies using Cr-Ni filler metals and Ni-based alloy. Results of AUGUR 4.2 inspection were compared with manual ultrasonic inspection ones in terms of defect detection, characterization, positioning and sizing in order to estimate correlation between these data. [Pg.195]

Correlation between amplitude or equivalent square data of manual control and defect height showed by AUGUR 4.2 was poor. [Pg.195]

Secondly, the linearized inverse problem is, as well as known, ill-posed because it involves the solution of a Fredholm integral equation of the first kind. The solution must be regularized to yield a stable and physically plausible solution. In this apphcation, the classical smoothness constraint on the solution [8], does not allow to recover the discontinuities of the original object function. In our case, we have considered notches at the smface of the half-space conductive media. So, notche shapes involve abrupt contours. This strong local correlation between pixels in each layer of the half conductive media suggests to represent the contrast function (the object function) by a piecewise continuous function. According to previous works that we have aheady presented [14], we 2584... [Pg.326]

The a priori information involved by this modified Beta law (5) does not consider the local correlation between pixels, however, the image f is mainly constituted from locally constant patches. Therefore, this a priori knowledge can be introduced by means of a piecewise continuous function, the weak membrane [2]. The energy related to this a priori model is ... [Pg.331]

The camera model has a high number of parameters with a high correlation between several parameters. Therefore, the calibration problem is a difficult nonlinear optimization problem with the well known problems of instable behaviour and local minima. In out work, an approach to separate the calibration of the distortion parameters and the calibration of the projection parameters is used to solve this problem. [Pg.486]

Fig. 4 illustrates the time-dependence of the length of top s water column in conical capillary of the dimensions R = 15 pm and lo =310 pm at temperature T = 22°C. Experimental data for the top s column are approximated by the formula (11). The value of A is selected under the requirement to ensure optimum correlation between experimental and theoretical data. It gives Ae =3,810 J. One can see that there is satisfactory correlation between experimental and theoretical dependencies. Moreover, the value Ae has the same order of magnitude as Hamaker constant Ah. But just Ah describes one of the main components of disjoining pressure IT [13]. It confirms the rightness of our physical arguments, described above, to explain the mechanism of two-side liquid penetration into dead-end capillaries. [Pg.617]

For applications on indications it is assumed that the visibility level VL of rectangular objects (indications) is the same as for circles with the same area. The lenght 1 and width w of indications are correlated in very different manners, mainly dependant on the geometrie of the inhomogenity (crack). From some observations, the following correlation between w and 1 was introduced w (mm) = 0.05 + 0.03 1 (e g. 1=1.5 mm, w a 0.1 mm). For the same areas, the length 1 of the indication can be introduced in Fig. 1 as a second scale. [Pg.670]

Fig. 4a shows a characteristic narrow banded signal (860 kHz center frequency) from a flat steel surface (reference signal). A steel block was milled in a way that the distance of the upper and graved surface varied from 0 to about 1300 microns (Fig. 5). Moving the probe along the edge (see Fig. 5) about 30 signals have been acquired equidistantly (all 4 mm). Fig. 4b and 4c show two characteristic signals (position 6 and 12). The 30 measured signals have been preprocessed and deconvolved. Fig. 6 shows the evident correlation between measured TOF difference and signal position (depth of milled grave). Fig. 4a shows a characteristic narrow banded signal (860 kHz center frequency) from a flat steel surface (reference signal). A steel block was milled in a way that the distance of the upper and graved surface varied from 0 to about 1300 microns (Fig. 5). Moving the probe along the edge (see Fig. 5) about 30 signals have been acquired equidistantly (all 4 mm). Fig. 4b and 4c show two characteristic signals (position 6 and 12). The 30 measured signals have been preprocessed and deconvolved. Fig. 6 shows the evident correlation between measured TOF difference and signal position (depth of milled grave).
At CSM Materialteknik AB the question has been raised whether the porosity estimation can be simplified further by utilizing attenuation measurements at a single frequency only. Empirical work show that for a given frequency, which is selcted based on the thickness of the inspected object, there is a correlation between the attenuation and the porosity contents. However, there has still not been any documented results proving that single frequency measurements are sufficient for porosity estimation. [Pg.886]

In Figure 4 the measured attenuation values (TT) and the corresponding estimates are plotted against each other. Ideally (with error free estimates) all sample points should lie on the straight line through the origin with unit slope. Clearly there is a strong correlation between the estimates and the true values. [Pg.891]

Barnes and co-workers have studied mixed-monolayer systems [278,281,283,284] and found some striking nonidealities. Mixed films of octadecanol and cholesterol, for example, show little evaporation resistance if only 10% cholesterol is present [278] apparently due to an uneven granular microstructure in films with cholesterol [284]. Another study of cellulose decanoate films showed no correlation between holes in the monolayer and permeation rate [285]. Polymerized surfactants make relatively poor water evaporation retarders when compared to octadecanol [286]. There are problems in obtaining reproducible values for r [287] due to impurities in the monolayer material or in the spreading solvent. [Pg.148]

The energetics and kinetics of film formation appear to be especially important when two or more solutes are present, since now the matter of monolayer penetration or complex formation enters the picture (see Section IV-7). Schul-man and co-workers [77, 78], in particular, noted that especially stable emulsions result when the adsorbed film of surfactant material forms strong penetration complexes with a species present in the oil phase. The stabilizing effect of such mixed films may lie in their slow desorption or elevated viscosity. The dynamic effects of surfactant transport have been investigated by Shah and coworkers [22] who show the correlation between micellar lifetime and droplet size. More stable micelles are unable to rapidly transport surfactant from the bulk to the surface, and hence they support emulsions containing larger droplets. [Pg.505]

Fig. XIV-10. The correlation between the HLB number and the phase inversion temperature in cyclohexane of nonionic surfactants. (From Ref. 71.)... Fig. XIV-10. The correlation between the HLB number and the phase inversion temperature in cyclohexane of nonionic surfactants. (From Ref. 71.)...
The structure of a fluid is characterized by the spatial and orientational correlations between atoms and molecules detemiiued through x-ray and neutron diffraction experiments. Examples are the atomic pair correlation fiinctions (g, g. . ) in liquid water. An important feature of these correlation functions is that... [Pg.437]

Fluctuations in the magnetization are ignored by mean-field theory and there is no correlation between neighbouring sites, so that... [Pg.533]


See other pages where Correlations between is mentioned: [Pg.216]    [Pg.79]    [Pg.199]    [Pg.221]    [Pg.266]    [Pg.3]    [Pg.39]    [Pg.244]    [Pg.446]    [Pg.625]    [Pg.888]    [Pg.454]    [Pg.486]    [Pg.524]    [Pg.466]    [Pg.476]    [Pg.548]    [Pg.549]    [Pg.549]    [Pg.679]    [Pg.699]   


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Ancient correlation between

Angular Correlations between Molecules

Anorthite correlation between

Asymptotic properties of correlations between chain ends Fishers result

Caco-2 cells correlation between fraction absorbed

Catalyst performance correlation between

Cellulose correlations between chemical shifts

Chemical correlation between

Cognitive abilities correlations between

Confounding and Correlation Between Parameters

Cooked potatoes correlations between

Correlated Relaxation for the Measurement of Projection Angles between Tensors

Correlation Between Adsorption Heat and Catalytic Activity

Correlation Between CEC and SAR

Correlation Between Electrophysiology and Radioligand Binding Studies

Correlation Between Morphology and Mechanical Properties

Correlation Between Nasal Drug Absorption Models

Correlation Between ORD and CD

Correlation Between Specific Surface and Overpotential of Electrodeposition

Correlation Between Two Sets of Data

Correlation and regression - relationships between measured values

Correlation between CBR and k value

Correlation between Electrical Conductivity

Correlation between Flow Behavior and Rheological Parameters

Correlation between Metal Particle Size and Reaction Mechanisms

Correlation between Molecular and Crystal Properties

Correlation between Propagation Length and Surface Roughness

Correlation between adhesion and

Correlation between adsorption behavior

Correlation between calcium and

Correlation between calculated and

Correlation between ceramic

Correlation between diffusion and entropy Adam-Gibbs

Correlation between elastic moduli from

Correlation between elastic moduli from values

Correlation between elastic modulus values

Correlation between energy

Correlation between fluorescence and structure

Correlation between fluorescence intensity and concentration

Correlation between formation

Correlation between glass transition induced

Correlation between initial

Correlation between kinetic data

Correlation between life spans, modeling

Correlation between local density and

Correlation between local density and binding energy

Correlation between o, x and

Correlation between parameter

Correlation between parameters for non-linear models

Correlation between product rotations

Correlation between protein

Correlation between protein concentration adsorption

Correlation between residuals and chemical class

Correlation between resilient modulus and CBR

Correlation between structure and spectroscopy of copper proteins

Correlation between the elastic constants of a highly oriented and an isotropic polymer

Correlation between the velocity and

Correlation between total lipophilicity

Correlation graph between various

Correlation, between analytical methods

Correlations Between Oxygen Diffusion Parameters

Correlations Between Polyethylene Properties

Correlations between (Bio-)Synthesis and Isotope Content or Pattern of Organic Compounds

Correlations between CBR and index properties of soil material

Correlations between Empirical Parameters and Other Measurable Solvent Properties

Correlations between Tm and

Correlations between Two and Three Protons

Correlations between chain ends

Correlations between diffusion coefficients and

Correlations between geometrical parameter

Correlations between metals

Correlations between structure and

Correlations between structure and dynamics

Correlations between the Schoenflies and Hermann-Mauguin symbols

Correlations between various

Crystallography, correlation between crystal

Dietary variables, correlation between

Dipoles correlations between

Direct correlation between grain boundary structure and electric transport properties

Distribution coefficients correlation between

Family correlations between

General Correlations between Electrode Potential and Current Density

Hardness indenters correlations between

Inhibitor correlation between

Lack of correlation between NP load and dementia

Measurements to Determine Angular Correlations between Ejected Electrons and Scattered Projectiles

Nitrogen bases, correlations between

Nitrogen, correlation between sulfur

Pair correlation function between monomers

Pericyclic reactions symmetry correlations between

Photochemical correlations between various

Poly correlation between crystalline

Polyimides correlation between diffusion coefficient

Possible Correlations between Homogeneous and Heterogeneous Catalysis

Quantitative Correlations Between Strain and Stability Differences

Quantitative relationships between structure empirical correlations

Solution-phase concentrations correlation between

Spin correlations between neighboring sites

Statistical correlation between

Statistical methods correlation between many data sets

Testosterone correlation between

The correlation between different normalisation methods

Thermodynamics of DNA-helix formation Correlation between enthalpy and entropy changes

Transition metal bases, correlation between

Valence Bond State Correlation Diagrams for Reactions between Nucleophiles and Electrophiles

Virus assays, correlation between

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