Empirical Approach to Defect Detection Probability by Acoustic Emission Testing

Estimation of probability of defect detection (POD) is one of the most important problems in acoustic emission (AE) testing. It is caused by the influence of the material microstructure parameters on the diagnostic data, variability of noises, the ambiguous assessment of the materials emissivity, and other factors, which hamper modeling the AE data, as well as the a priori determination of the diagnostic parameters necessary for calculating POD. In this study, we propose an empirical approach based on the generalization of the experimental AE data acquired under mechanical testing of samples to a priori estimation of the AE signals emitted by the defect. We have studied the samples of common industrial steels 09G2S (similar to steel ANSI A 516-55) and 45 (similar to steel 1045) with fatigue cracks grown in laboratory conditions during cyclic testing. Empirical generalization of data using probabilistic models enables estimating the conditional probability of record emissivity and amplitudes of AE signals. This approach allows to eliminate the existing methodological gap and to build a comprehensive method for assessing the probability of fatigue cracks detection by the AE testing.

Physical controls and a priori estimation of raising land surface elevation across the southwestern Bangladesh delta using Tidal River Management

The Ganges-Brahmaputra-Meghna delta in Bangladesh is one of the largest and most populated deltas in the world and threatened by relative sea level rise (RSLR). Renewed sediment deposition through tidal river management (TRM), a controlled flooding with dike breach, inside the lowest parts of the delta polders (so-called “beels”) can potentially counterbalance RSLR. The potential of TRM application in different beels across southwestern Bangladesh, however, still remains to be determined. We used a 2D morphodynamic model to explore the physical controls of five variables on total sediment deposition inside the beels during TRM: river tidal range (TR), river suspended sediment concentration (SSC), inundation depth (ID), width of the inlet (IW) and surface area of the beel (BA). Non-linear regression models (NLMs) were developed using the results of 2D models to quantify how sediment deposition inside the beels depends on these variables. The NLMs have an average coefficient of determination of 0.74 to 0.77. Application of the NLMs to 234 beels of southwestern Bangladesh indicates that TRM operation in beels located closer to the sea will retain more sediment as a result of decreasing SSC further inland. Beels in the western part retain more sediment because of lower average land surface elevation. Smaller beels have higher potential to raise land surface elevation due to nonlinear increase of sediment deposition per day (SPD) with beel area. Compartmentalization of larger beels may increase their potential to raise land surface elevation. Thus, the length of time of TRM application in cyclic order will need to vary across the delta to counterbalance RSLR, depending on current beel land surface elevation and local TRM sediment accumulation rates. We found that operating TRM only during the monsoon season is sufficient to raise land surface in 96 % and 80 % of all beels by more than 3 and 5 times the yearly RSLR, respectively. Applying TRM only seasonally offers huge advantages as to keeping the land available for agriculture during the rest of the year. The methodology presented here applying regression models based on 2D morphodynamic modeling may be used for the low-lying sinking deltas around the world to provide an a-priori estimation of sediment deposition from controlled flooding to counterbalance RSLR.

Determination of the Spatial Resolution of Radar Images in Remote Sensing of the Earth

Introduction. The analysis of the current state and prospects of space-based radar surveillance tools is important for determining their functions in global aerospace information systems, which aim to monitor air and space, as well as the Earth's surface. Radar surveillance information is used for the purposes of economic analysis, environmental monitoring, mineral search, emergency monitoring, detection and recognition of specified object s at sea and on land, as well as for ensuring national security. In this regard, it is of relevance to develop methods for preliminary assessment of the resolution capacity of novel high-precision onboard radar systems installed on a spacecraft, considering their main technical characteristics, the parameters of the spacecraft movement and the influence of the atmosphere. A priori estimation of spatial resolution values requires a method for calculating the corresponding indicators meeting the required quality of the synthesized radio holograms.Aim. To derive mathematical dependencies and logical rules allowing a priori estimation of the spatial resolution of radar images obtained by the onboard equipment of a radar complex.Materials and methods. Analytical methods were used to determine the resolution error of onboard radar systems with a synthesized aperture in the lateral (azimuthal) direction and range, as well as the theory of radar signal processing.Results. A comparison of the experimental and analytical data on the resolution capacity of an actual radar system confirmed the validity on the proposed method. The developed methodology was used to determine the procedure of calculating the error when estimating the resolution capacity in terms of azimuth and range. Conclusion. The proposed method can be used for both designing novel radar systems and comparing existing radar complexes, depending on the resolution requirements.

ON ALGORITHM FOR DETECTING CHANGES IN THE OBJECT MOTION MODE

The article deals with the solution to the problem of determining the motion mode of an object along a complex trajectory. A hybrid stochastic model is used to describe a complex trajectory. The solution of the problem is based on the application of a sequential decision rule about the choice at an unknown time of the hypothesis about the current mode of motion, with a limited size of the bank of competing Kalman filters. An algorithm is constructed for calculating the average size of the Kalman filter bank in the case of M-possible motion modes. The algorithm is developed in a general form, therefore, it can be used not only for the four types of object motion models considered in this paper, but also for any linear discrete-time models with Gaussian noise presented by equations in the state space. The algorithm for a priori estimation of the average size of a bank of competing Kalman filters for M-possible modes of motion is implemented in MATLAB, the results of computer simulation are presented.