990 resultados para Importance Sampling
Resumo:
A 37-m thick layer of stratified clay encountered during a site investigation at Swann's Bridge, near the sea-coast at Limavady, Northern Ireland, is one of the deepest and thickest layers of this type of material recorded in Ireland. A study of the relevant literature and stratigraphic evidence obtained from the site investigation showed that despite being close to the current shoreline, the clay was deposited in a fresh-water glacial lake formed approximately 13 000 BP. The 37-m layer of clay can be divided into two separate zones. The lower zone was deposited as a series of laminated layers of sand, silt, and clay, whereas the upper zone was deposited as a largely homogeneous mixture. A comprehensive series of tests was carried out on carefully selected samples from the full thickness of the deposit. The results obtained from these tests were complex and confusing, particularly the results of tests done on samples from the lower zone. The results of one-dimensional compression tests, unconsolidated undrained triaxial tests, and consolidated undrained triaxial compression tests showed that despite careful sampling, all of the specimens from the lower zone exhibited behaviour similar to that of reconstituted clays. It was immediately clear that the results needed explanation. This paper studies possible causes of the results from tests carried out on the lower Limavady clay. It suggests a possible mechanism based on anisotropic elasticity, yielding, and destructuring that provides an understanding of the observed behaviour.Key words: clay, laminations, disturbance, yielding, destructuring, reconstituted.
Resumo:
It is shown that virtual H- formation has a profound effect upon low-energy Ps(1s)-H(1s) scattering, yet H- formation only accounts for about 10% of the total cross section just above threshold. Infinite series of Rydberg resonances converging on to the H- formation threshold are seen.
Resumo:
The results of a study aimed at determining the most important experimental parameters for automated, quantitative analysis of solid dosage form pharmaceuticals (seized and model 'ecstasy' tablets) are reported. Data obtained with a macro-Raman spectrometer were complemented by micro-Raman measurements, which gave information on particle size and provided excellent data for developing statistical models of the sampling errors associated with collecting data as a series of grid points on the tablets' surface. Spectra recorded at single points on the surface of seized MDMA-caffeine-lactose tablets with a Raman microscope (lambda(ex) = 785 nm, 3 mum diameter spot) were typically dominated by one or other of the three components, consistent with Raman mapping data which showed the drug and caffeine microcrystals were ca 40 mum in diameter. Spectra collected with a microscope from eight points on a 200 mum grid were combined and in the resultant spectra the average value of the Raman band intensity ratio used to quantify the MDMA: caffeine ratio, mu(r), was 1.19 with an unacceptably high standard deviation, sigma(r), of 1.20. In contrast, with a conventional macro-Raman system (150 mum spot diameter), combined eight grid point data gave mu(r) = 1.47 with sigma(r) = 0.16. A simple statistical model which could be used to predict sigma(r) under the various conditions used was developed. The model showed that the decrease in sigma(r) on moving to a 150 mum spot was too large to be due entirely to the increased spot diameter but was consistent with the increased sampling volume that arose from a combination of the larger spot size and depth of focus in the macroscopic system. With the macro-Raman system, combining 64 grid points (0.5 mm spacing and 1-2 s accumulation per point) to give a single averaged spectrum for a tablet was found to be a practical balance between minimizing sampling errors and keeping overhead times at an acceptable level. The effectiveness of this sampling strategy was also tested by quantitative analysis of a set of model ecstasy tablets prepared from MDEA-sorbitol (0-30% by mass MDEA). A simple univariate calibration model of averaged 64 point data had R-2 = 0.998 and an r.m.s. standard error of prediction of 1.1% whereas data obtained by sampling just four points on the same tablet showed deviations from the calibration of up to 5%.