Severity-distribution analysis

Severity-distribution analysis is used in estimations of the probability of severe accidents at a workplace and in comparing different workplaces with respect to the expected severity of the accidents (Briscoe, 1982). 

A severity-distribution analysis is based on the accidents for a specified 

1 Arrange the accidents by consequence (e.g. the number of days of absence) in an ascending order. 

2 Divide the highest registered consequence value into intervals such that each interval has approximately the same size on a logarithmic scale. Table 15.4 shows an example. 

3 Tally the number of accidents in each interval and the cumulative number (see Table 15.4). 

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Table 15.4 Severity-distribution analysis of accidents at a steel mill. N is the total number of accidents...

Extreme-value projection has some similarities to severity distribution analysis but utilises the most severe case for each period only (Briscoe, 1982). This can be a month, quarter or year. The value of this method lies in the possibility of anticipating how long a time we may expect it to take until the company experiences a really severe accident, e.g. a fatality or an accident involving major monetary loss. This is done through extrapolation based on data from less severe accidents. The method also gives input to an evaluation of whether a company has adequate control of its accident risks or not. Extreme-value projection utilises advanced statistics but is relatively simple to use in practice by applying special plotting paper. 

Severity-distribution analysis of accidents at a steel mill 217... 

Several numerical procedures for EADF evaluation have also been proposed. Morrison and Ross [19] developed the so-called CAEDMON (Computed Adsorption Energy Distribution in the Monolayer) method. Adamson and Ling [20] proposed an iterative approximation that needs no a priori assumptions. Later, House and Jaycock [21] improved that method and proposed the so-called HILDA (Heterogeneity Investigation at Loughborough by a Distribution Analysis) algorithm. Stanley et al. [22,23] presented two regularization methods as well as the method of expectation maximalization. 

The obtained STPP liposomes were characterized by size distribution analysis, P NMR spectroscopy (Fig. 3), and by zeta potential measurements (Fig. 4). The size of liposomes with 20 mol% incorporated STPP was determined to be 132 zb 59 nm, which did not change significantly upon storage at 4°C over several days. The P NMR spectrum of STPP liposomes shows two chemical shifts correlating to the phosphorus in the lipid s phosphate groups and to the positively charged phosphorus of STPP. No differences in both chemical shifts between the free compounds (i.e., free STPP and free... 

The extraction of more complex particle size distributions from PCS data (which is not part of the commonly performed particle size characterization of solid lipid nanoparticles) remains a challenging task, even though several corresponding mathematical models and software for commercial instruments are available. This type of analysis requires the user to have a high degree of experience and the data to have high statistical accuracy. In many cases, data obtained in routine measurements, as are often performed for particle size characterization, are not an adequate basis for a reliable particle size distribution analysis. 

LA-ICP-MS enables images to be produced of the distribution of essential elements such as Zn, Cu, Fe, S, P, Se and Mn as well as of toxic and also radioactive metals (e.g., Hg, Pb, Cd, Th and U) in thin tissue sections with a spatial resolution in the (im range. This spatial resolution of element distribution analysis is sufficient to distinguish between several layered structures in human brain tissue from the hippocampus, as described by Zilles et al.162... 

While scant literature is available on persistence and distribution after inhalation exposure, several studies have evaluated the systemic behavior of parenterally administered toxins. One group investigated toxin persistence in serum and tissue distribution in white mice following intravenous (IV) administration of 1,000 lethal doses of S-labeled type B toxin (Pak and Bulatova, 1962). Mice were sacrificed at 20, 60, and 150 min after toxin administration, and blood and tissues were harvested for toxin distribution analysis. These mice showed symptoms of severe intoxication, including atypical breathing patterns and paralysis, at 150 min post-exposure. Toxin levels (as determined by... 

The application of the Weibull distribution for describing lifetime has been proved in several preceded analysis and was therefore applied to fit the empirical warranty data. The usage of other theoretical distribution functions, such as the lognormal distribution, is also suitable to describe the lifetime but was not considered in this analysis. See (Meyna Pauh 2003) for more detailed information. 

Several distribution laws for frequency-magnitude of rockfalls have been proposed, based on the statistical analysis of series of past events (Hungr et al., 1999). Many studies have shown that the frequency-magnitude distributions of rock falls from limited homogeneous areas are well fitted by a power law (Hungr et al., 1999 and Dussauge et al., 2002, 2003). Many studies use a logarithmic attempt. 

Figure 15.7 shows an example of a distribution analysis of the accidents at a steel mill. The slope of the straight regression line is an indicator of how probable it is that an accident will result in severe consequences. The higher the slope, the higher is this probability. In the case illustrated by the figure, there is a probability of about 0.02 that an accident will result in more than 100 days of absence. 

In order to perform the lifetime distribution analysis, several decay curves in different instrumental time scales were recorded. A superposition of those decay traces was made by normalization of each decay curve at a time range where they overlap, in order to produce a composite decay with closely spaced data at short times and larger spaced values at long times. This procedure was adopted before [14, 19], and is necessary because the abscissa is In t, therefore a very large time range had to be used. 

The control technique of fuel distribution in uranium - graphite fiael elements seems to be most perform. The technique allows to determine weight of uranium or its connections in a chosen zone of fuel elements. There were used the sources of radiation on a basis radionuclide Am. The weight of uranium in fuel element or its parts is determined by combine processing of a tomograms, set received on several parallel layers of fuel element. The comparative results of tomographic researches and chemical analysis of weight of uranium in quarters of spherical fuel elements are resulted in the table. 

Lamellar morphology variables in semicrystalline polymers can be estimated from the correlation and interface distribution fiinctions using a two-phase model. The analysis of a correlation function by the two-phase model has been demonstrated in detail before [30,11] The thicknesses of the two constituent phases (crystal and amorphous) can be extracted by several approaches described by Strobl and Schneider [32]. For example, one approach is based on the following relationship ... 

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