Dynamic calibration for multi-beam bathymetric system based on characteristic data processing
The geometric installation error of the multi-beam bathymetric system will affect measure accuracy of the depth and location, which must be faced and resolved in the engineering survey urgently. The most important three kinds of the installation error are roll error, pitch error and yaw error. Through quantitative analysis of impact of installation error to the measure result, a dynamic calibration method has been proposed in the paper. In the method, installation errors can be obtained by analyzing bathymetric result from the characteristic terrain seafloor and the errors will be used as the parameters to calibrate other bathymetric result. Validity of the method has been proved by processing the measure data from Songhua Lake test.
Integrated error correction of multi-beam marginal sounding beam
The error of marginal beams mainly influences the quality of multi-beam sounding data. The precision of multi-beam sounding data influences their reliability and application, and it is the base of correlative study. The key control factors of marginal beams quality are accurate multi-beam sonar parameters, accurate sound profiles and sounding noises compilation. If inaccurate multi-beam sonar parameters or inaccurate sound profiles are used in flat area during the multi-beam survey, unreality submarine topography will be got such as belt along the survey line. It is difficult to improve the quality of multi-beam sounding data using single method during post-processing, because the error of multi-beam sounding is caused by different factors. On the basis of multi-beam survey principles and the acoustics theory, the multi-beam sounding error data have been researched and processed, the software of man-machine conversation to process the multi-beam error sounding data has been designed and estahlished with oriented-object method of GIS at last. The study result has been used in topographic mapping of marin project.
A comparison of experimental thermal stratification parameters for an oil/pebble-bed thermal energy storage (TES) system during charging
Six different experimental thermal stratification evaluation parameters during charging for an oil/pebble-bed TES system are presented. The six parameters are the temperature distribution along the height of the storage tank at different time intervals, the charging energy efficiency, the charging exergy efficiency, the stratification number, the Reynolds number and the Richardson number. These parameters are evaluated under six different experimental charging conditions. Temperature distribution along the height of the storage tank at different time intervals and the stratification number are parameters found to describe thermal stratification quantitatively adequately. On the other-hand, the charging exergy efficiency and the Reynolds number give important information about describing thermal stratification qualitatively and should be used with care. The charging energy efficiency and the Richardson number have no clear relationship with thermal stratification.