No abstract

Ultrasonic guided waves are one of the primary methods being investigated for structural health monitoring of plate-like components. A common practice is to collect measurements from a sparse transducer array using the pitch-catch method, which enables interrogation of defects from multiple directions. Thus, knowledge of how guided waves scatter from defects is very useful for detection, localization, and characterization of damage. One way to describe scattering patterns is with a matrix indexed by incident angle and scattered angle, and sparse array measurements essentially sample this matrix. A methodology is proposed in this paper to estimate the complete scattering matrix from these limited array measurements. First, recorded array signals are compensated for geometric spreading loss, wave packet spreading loss, and transducer differences. Initial scattering values are then extracted from the scattered wave packets after baseline subtraction and are augmented using transducer reciprocity and any a priori knowledge of defect geometric symmetry. Finally, radial basis function interpolation is performed on these values to obtain the complete scattering matrix. Scattering matrices are generated from experimental data by cutting notches of different lengths originating from a through-hole in an aluminum plate specimen that is instrumented with a sparse transducer array. The methodology is validated by laser vibrometry measurements performed on a nominally identical specimen for one notch length.

No abstract

No abstract

Large-scale climate history of the past millennium reconstructed solely from tree-ring data is prone to underestimate the amplitude of low-frequency variability. In this paper, we aimed at solving this problem by utilizing a novel method termed “MDVM”, which was a combination of the ensemble empirical mode decomposition (EEMD) and variance matching techniques. We compiled a set of 211 tree-ring records from the extratropical Northern Hemisphere (30–90°N) in an effort to develop a new reconstruction of the annual mean temperature by the MDVM method. Among these dataset, a number of 126 records were screened out to reconstruct temperature variability longer than decadal scale for the period 850–2000 AD. The MDVM reconstruction depicted significant low-frequency variability in the past millennium with evident Medieval Warm Period (MWP) over the interval 950–1150 AD and pronounced Little Ice Age (LIA) cumulating in 1450–1850 AD. In the context of 1150-year reconstruction, the accelerating warming in 20th century was likely unprecedented, and the coldest decades appeared in the 1640s, 1600s and 1580s, whereas the warmest decades occurred in the 1990s, 1940s and 1930s. Additionally, the MDVM reconstruction covaried broadly with changes in natural radiative forcing, and especially showed distinct footprints of multiple volcanic eruptions in the last millennium. Comparisons of our results with previous reconstructions and model simulations showed the efficiency of the MDVM method on capturing low-frequency variability, particularly much colder signals of the LIA relative to the reference period. Our results demonstrated that the MDVM method has advantages in studying large-scale and low-frequency climate signals using pure tree-ring data.