Ultrasonic fingerprinting by phased array transducer

Increasing quantity of spent nuclear fuel that must be under national and international control requires a novel approach to safeguard techniques and equipment. One of the proposed approaches is utilize intrinsic features of casks with spent fuel. In this article an application of a phased array ultrasonic method is considered. This study describes an experimental results on ultrasonic fingerprinting of austenitic steel seam weld

Ultrasonic fingerprinting by phased array transducer

Increasing quantity of spent nuclear fuel that must be under national and international control requires a novel approach to safeguard techniques and equipment. One of the proposed approaches is utilize intrinsic features of casks with spent fuel. In this article an application of a phased array ultrasonic method is considered. This study describes an experimental results on ultrasonic fingerprinting of austenitic steel seam weld

Smart manufacturing of complex shaped pipe components

Manufacturing industry is constantly improving. Nowadays the most relevant trend is widespread automation and optimization of the production process. This paper represents a novel approach for smart manufacturing of steel pipe valves. The system includes two main parts: mechanical treatment and quality assurance units. Mechanical treatment is performed by application of the milling machine with implementation of computerized numerical control, whilst the quality assurance unit contains three testing modules for different tasks, such as Xray testing, optical scanning and ultrasound testing modules. The advances of each of them provide reliable results that contain information about any failures of the technological process, any deviations of geometrical parameters of the valves. The system also allows detecting defects on the surface or in the inner structure of the component

Combined cloud-microwave radiative transfer modeling of stratiform rainfall

The simulation of explicit particle spectra during cloud evolution by a two-dimensional spectral cloud model was used to investigate the response of microwave radiative transfer to particle spectra development with special focus on the radiative effects of melting particles below the freezing level. For this purpose, 1) a particle-melting model was implemented with increased vertical resolution; 2) several models of the dielectric permittivity for melting particles were compared; 3) the dependence on size–density distributions was evaluated; and 4) the influence on the results by the replacement of explicit by parameterized particle spectra was tested. Radiative transfer simulations over ocean background at frequencies between 10.7 and 85.5 GHz showed a considerable increase in brightness temperatures (TB) once melting particles were included. The amounts were strongly dependent on the implemented permittivity model, the number concentrations of large frozen particles right above the freezing level, and the local cloud conditions. Assuming a random mixture of air, ice, and meltwater in the particle, TBs increased by up to 30 K (at 37.0 GHz) in the stratiform cloud portion for nadir view. If the meltwater was taken to reside at the particle boundaries, unrealistic TB changes were produced at all frequencies. This led to the conclusion that for large tenuous snowflakes the random-mixture model seems most appropriate, while for small and dense particles a nonuniform water distribution may be realistic. The net melting effect on simulated TBs, however, depended strongly on attenuation by supercooled liquid water above the freezing level, which generally suppressed the signal at 85.5 GHz. Over land background, changes in TB due to melting particles remained below 8 K, which would be difficult to identify compared to variations in surface emission and cloud profile heterogeneity. Replacement of the explicit particle spectra for rain, snow, and graupel by parameterized spectra (here, in exponential form with a fixed intercept) produced reductions of the melting signature by up to 40% over ocean. It was found that exponential size distribution formulas tended to underestimate number concentrations of large particles and overestimated those of small particles at those cloud levels where sufficient particle sedimentation leads to collection, aggregation, and evaporation, respectively. Consequently, the strongest differences between explicit and parameterized spectra occurred right above the freezing level for snow and graupel, and close to the surface for rain. Radiometrically, this resulted in an underestimation of scattering above the freezing level and an underestimation of emission by melting particles below the freezing level as well as by rain toward the surface. In the stratiform region, the net effect was a reduction of the melting signature; however, TB’s were still up to 15 K higher than from the no-melting case for the random-mixture permittivity model

N

RNA-cleaving deoxyribozymes can serve as selective sensors and catalysts to examine the modification state of RNA. However, site-specific endonuclease deoxyribozymes that selectively cleave posttranscriptionally modified RNA are extremely rare and their specificity over unmodified RNA is low. In this study, we report that the native tRNA modification N$^6$-isopentenyladenosine (i$^6$A) strongly enhances the specificity and has the power to reconfigure the active site of an RNA-cleaving deoxyribozyme. Using in vitro selection, we identified a DNA enzyme that cleaves i$^6$A-modified RNA at least 2500-fold faster than unmodified RNA. Another deoxyribozyme shows unique and unprecedented behaviour by shifting its cleavage site in the presence of the i$^6$A RNA modification. Together with deoxyribozymes that are strongly inhibited by i$^6$A, these results highlight intricate ways of modulating the catalytic activity of DNA by posttranscriptional RNA modifications