Non-iterative mode shape expansion for three-dimensional structures based on coordinate decomposition

The direct mode shape expansion method is an iterative technique, one can conclude that the convergence performance maybe challenged when applied to three-dimensional structures. In addition, mode shape values at different DOFs (degrees-of-freedom) sometimes are not in a same order of magnitude, which will produce much error for the estimation of small values of unmeasured mode components. Therefore this paper proposed a non-iterative mode shape expansion method based on coordinate decomposition technique. The advantage of coordinate decomposition is that the unmeasured components of mode shape values could be estimated with different weighting coefficients, even in a physical meaningful interval. Numerical studies in this paper are conducted for a 30-DOF cantilever beam with multiple damaged elements, as the measured modes are synthesized from finite element models. The numerical results show that the approach can estimate unmeasured mode shape values at translational and rotational DOFs in x, y and z directions with different weighting coefficients, respectively; and better mode shape expansion results can be obtained when proper constraints are employed. A numerical three dimensional structure is also investigated, and results indicate that the estimation of unmeasured components can be improved by imposing reasonable constraints based on the coordinate decomposition technique, even only translational DOFs of two diagonal nodes of the first floor are measured

The effect of inclination on vortex-induced vibration of a circular cylinder with a base column

The vortex-induced vibration (VIV) of an inclined cylinder can be affected by its end condition. This paper numerically investigates the effect of inclination on the VIV of an elastically mounted rigid cylinder with a base column, which derives from a floating offshore wind turbine (FOWT). The numerical methods are validated against an existing VIV study of a finite-length cylinder. Two inclination angles, i.e. -5° and -10°, are studied to simulate the relatively small wind-induced inclination experienced by FOWTs. Results from stationary simulations show that differences between the force coefficients of inclined and upright cylinders are rather small. Nevertheless, contrary to the finding from previous VIV studies that the effect of inclination on the response of a cylinder with small inclination angles is limited, the present investigation reveals that the maximum response amplitude of the cylinder increases by about 20% when the inclination angle grows to -10° due to the presence of the base column. Meanwhile, the inclination leads to a reduction in the width of the lock-in regime. The impacts of inclination are further discussed via forced vibration studies with same oscillation parameters, which show that the upper part of the cylinder is more affected by the inclination compared to the base column with a considerable decrease in the amplitude of lift coefficient. The discrepancies in fluid forces are substantiated by analysing the pressure distribution on specified spanwise sections of the cylinder surface

A new time-frequency analysis method based on single mode function decomposition for offshore wind turbines

The Hilbert-Huang transform (HHT) has been widely applied and recognised as a powerful time-frequency analysis method for nonlinear and non-stationary signals in numerous engineering fields. One of its major challenges is that the HHT is frequently subject to mode mixing in the processing of practical signals such as those of offshore wind turbines, as the frequencies of offshore wind turbines are typically close and contaminated by noise. To address this issue, this paper proposes a new timefrequency analysis method based on single mode function (SMF) decomposition to overcome the mode mixing problem in the structural health monitoring (SHM) of offshore wind turbines. In this approach, the structural vibration signal is first decomposed into a set of window components using complex exponential decomposition. A state-space model is introduced in the signal decomposition to improve the numerical stability of the decomposition, and then a novel windowalignment strategy, named energy gridding, is proposed and the signals are constructed in the corresponding gridding. Furthermore, energy recollection is implemented in each gridding, and the reassembling of these components yields an SMF that is comparable to the intrinsic mode function (IMF) of the HHT, but with a significant improvement in terms of mode mixing. Four case studies are conducted to evaluate the performance of the proposed method. The first case attempts to detect three different frequencies in a simulated time-invariant signal. The second case attempts to test a synthesised signal with segmental time-varying frequencies (each segment contains three different frequencies components). The analysis results in these two cases indicate that mode mixing can be reduced by the proposed method. Furthermore, a synthesised signal with slowly varying frequencies is used. These analysis results demonstrate the effective suppression of non-relevant frequency components using SMF decomposition. In the third case, the experimental data from vortex-induced vibration (VIV) experiments sponsored by the Norwegian Deepwater Programme (NDP) are used to evaluate the proposed SMF decomposition for vibration mode identification. In the final case, field data acquired from an offshore wind turbine foundation and offshore wind turbine are analysed. The mode identification results obtained using SMF decomposition are compared with those produced by the HHT. The comparison demonstrates superior performance of the proposed method in identifying the vibration modes of the VIV experimental and field data

A signal decomposition method based on repeated extraction of maximum energy component for offshore structures

Contrary to most signal decomposition methods that usually decompose an original signal into a series of components simultaneously, a novel approach based on repeated extraction of Maximum Energy Component (MEC) is proposed. The approach starts from determination of the MEC referring to the estimated Power Spectral Density (PSD) function, and then represents the MEC by employing an exponential function to fit the original signal. By defining a stopping criterion based on two adjacent estimated PSDs, each MEC can be accurately extracted with an improved performance throughout the entire signal decomposition. To verify the proposed method, a single degree-of-freedom system subject to harmonic loads has been examined. Numerical results show that the analytical response can not only be decomposed into four MECs corresponding to the excitation and the system, respectively, but also provide an accurate estimation of natural frequency and damping ratio of the system. Meanwhile, by observing results from the Ensemble Empirical Mode Decomposition (EEMD), Variational Mode Decomposition (VMD) and Prony based on state-space model (Prony-SS), an improved decomposition accuracy has been achieved from the proposed approach. Furthermore, experimental data from the Norwegian Deepwater Programme and two sets of field-test data from one fixed offshore platform and an offshore wind turbine have been used to demonstrate the correctness of the developed signal decomposition method. It is noted that divergence in results by Prony-SS can be observed when a very large model order is used, while the proposed method provides the better decomposition and reconstruction of signals

Coupling of carbon and silicon geochemical cycles in rivers and lakes

Carbon (C) and silicon (Si) biogeochemical cycles are important factors in the regulation of atmospheric CO2 concentrations and hence climate change. Theoretically, these elements are linked by chemical weathering and organism stoichiometry, but this coupling has not been investigated in freshwaters. Here we compiled data from global rivers and lakes in the United States of America and the United Kingdom, in order to characterize the stoichiometry between the biogeochemical cycles of C and Si. In rivers this coupling is confirmed by a significant relationship between HCO3-/Na+ and DSi/Na+, and DSi:HCO3- ratio can reflect the mineral source of chemical weathering. In lakes, however, these characteristic ratios of chemical weathering are altered by algal activity. The lacustrine Si:C atomic ratio is negative feedback regulation by phytoplankton, which may result in this ratio in algal assemblages similar to that in water column. And this regulation suggests lacustrine photosynthetic C fixation in this equilibrium state is quantitative and depends on the DSi concentration. These findings provide new insights into the role of freshwaters in global C and Si biogeochemical cycles

A novel physics-informed framework for reconstruction of structural defects

Ultrasonic guided wave technology has played a significant role in the field of non-destructive testing as it employs acoustic waves that have advantages of high propagation efficiency and low energy consumption during the inspect process. However, theoretical solutions to guided wave scattering problems using assumptions such as Born approximation, have led to the poor quality of the reconstructed results. Moreover, scattering signals collected from industry sectors are often noised and nonstationary. To address these issues, a novel physics-informed framework (PIF) for quantitative reconstruction of defects using the integration of data-driven method with the guided wave scattering analysis has been proposed in this paper. Based on the geometrical information of defects and initial results obtained by PI-based analysis of defect reconstructions, a deep learning neural network model is built to reveal the physical relationship between defects and the noisy detection signals. This data-driven learning model is then applied to quantitatively assess and characterize defect profiles in structures, improve the accuracy of the analytical model and eliminate the impact of noise pollution in the process of inspection. To demonstrate advantages of the developed PIF for complex defect reconstructions with the capability of denoising, numerical examples including basic defect profiles, a stepped defect, a mixed-type defect have been examined. Results show that PIF has greater accuracy for reconstruction of defects in structures as compared with the analytical method and provides a valuable insight into the development of artificial intelligence-assisted inspection systems with high accuracy and efficiency in the fields of structural integrity and condition monitoring

The effect of base column on vortex-induced vibration of a circular cylinder with low aspect ratio

The end condition of a cylinder is known to influence its vortex-induced vibration (VIV) response. The design of a short circular cylinder with a concentric base column attached to its bottom is adopted by some floating structures for improved stability, but how the base column would affect the VIV of the cylinder has been rarely studied. In this paper, the VIV of an elastically mounted rigid cylinder with a base column and a low aspect ratio of 2 is investigated numerically by solving the Navier-Stokes equations. The numerical methods are validated against two existing VIV studies, including a 2D cylinder and a cylinder with a finite length. The impacts of the base column on the cylinder are analysed. It is found that although the free end effects associated with fluid flowing around the cylinder end are still present, attaching the base column leads to the expansion of the lock-in regime of the cylinder response. A relationship between non-dimensional response amplitude and lift coefficient is established, which takes into consideration the geometrical properties of the base column. By analysing the energy transfer from fluid to structure, the base column is also found to have significant damping effects on the cylinder response

Evidence against a role for jaagsiekte sheep retrovirus in human lung cancer

Background: Jaagsiekte sheep retrovirus (JSRV) causes a contagious lung cancer in sheep and goats that can be transmitted by aerosols produced by infected animals. Virus entry into cells is initiated by binding of the viral envelope (Env) protein to a specific cell-surface receptor, Hyal2. Unlike almost all other retroviruses, the JSRV Env protein is also a potent oncoprotein and is responsible for lung cancer in animals. Of concern, Hyal2 is a functional receptor for JSRV in humans. Results: We show here that JSRV is fully capable of infecting human cells, as measured by its reverse transcription and persistence in the DNA of cultured human cells. Several studies have indicated a role for JSRV in human lung cancer while other studies dispute these results. To further investigate the role of JSRV in human lung cancer, we used highly-specific mouse monoclonal antibodies and a rabbit polyclonal antiserum against JSRV Env to test for JSRV expression in human lung cancer. JSRV Env expression was undetectable in lung cancers from 128 human subjects, including 73 cases of bronchioalveolar carcinoma (BAC; currently reclassified as lung invasive adenocarcinoma with a predominant lepidic component), a lung cancer with histology similar to that found in JSRV-infected sheep. The BAC samples included 8 JSRV DNA-positive samples from subjects residing in Sardinia, Italy, where sheep farming is prevalent and JSRV is present. We also tested for neutralizing antibodies in sera from 138 Peruvians living in an area where sheep farming is prevalent and JSRV is present, 24 of whom were directly exposed to sheep, and found none. Conclusions: We conclude that while JSRV can infect human cells, JSRV plays little if any role in human lung cancer