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BenDavid et al., this volume) and India (Schrauder et al. unpublished data). The fluid composition varies between three end-members: carbonatitic melts, rich in carbonate, Ca, Fe, Mg, K and P; Hydrous-silicic melts, rich in Si, water, Al and K and brine rich in water, Cl and K. Here we report new data from micro-inclusion bearing diamonds from Brazil. The micro-inclusions contain melts that span the range between carbonatitic and hydro-silicic compositions. The entire range between the two end members is observed in single diamonds. Thus, in two diamonds, it is possible to follow the evolution of the melt during diamond growth.

This study presents the algorithms, the criteria, and some important computing formulas used for visualization of acoustic-emission sources in tests of pipelines and vessels operated under pressure. These means of visualization also include the instruments for computer processing and presentation of the data on acoustic-emission tests, which can be useful for solving both linear-and planar-source location problems. During analysis of the inspection results of the above-mentioned objects, these facilities were evaluated on the basis of post-processed data that was obtained by various measuring and computing acoustic-emission complexes.One of the most important advantages of acoustic-emission (AE) tests is the possibility of determining the coordinates and visualizing sources (flaws), thus providing a graphic representation (imaging) of the arrangement of radiation sources over the inspected object. The reliability of the tests depends significantly on the adequacy of such visualization. The objective of this study is to describe the algorithms and criteria and to represent some important computing formulas and expressions evaluated for point location of AE sources during the inspection of pipelines and vessels operated under pressure.The main aspects of formulating and solving the problem of determining AE-source coordinates by the signal-arrival time at spaced detectors (AE-signal transducers) are considered in detail in [1]. Without discussing these results in detail here, let us consider some new aspects pertaining to solution and practical use of the solutions to the problems of source location and visualization.Let us begin with linear (one-dimensional) location, where the position of an AE source is determined by one number that characterizes the lengthwise distancing of this source from some specific point, this point being accepted as the origin. It is assumed that a transverse shift of a source in the inspected object is insignificant.In particular, for example, for a pipeline section, whose length significantly exceeds its cross-sectional dimensions, the problem of linear location can be formulated as follows.We suggest that an elastic pulse be radiated from point x S of a pipeline section and the pulse be detected at moments t i by the system of spaced AE transducers set at points of observation x i ( i = 1, 2, 3, etc.). The velocity of sound in the inspected object, c sn , is known. On the basis of signal detection time t i , x S should be found. The solution to this problem can be expressed as (1) Apparently, at least two spaced transducers (AE detectors) i and j detecting a pulse are required for linear location, provided that x i ≤ x S ≤ t j and (2) Thus, if the difference in arrival times (DAT) is abs ( t i -t j ) > t max for two pulses detected by two AE detectors i and j and condition (2) is not fulfilled, the pulses must be regarded spatially uncorrelated, which means that they are not related to the same source positioned inside a location cell in segment [ x i , x j ].Despite solution (1) look...

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