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Offshore Wind Turbines (OWTs) are dynamically sensitive structures and as a result estimating the natural frequency of the whole system taking into effect the flexibility of the foundation is one of the major design considerations. The natural frequency is necessary to predict the long-term performance as well as the fatigue life. OWTs are currently being constructed in seismically active regions such as the United States, China, India and Taiwan and there is a need for design considerations for OWTs located in seismic zones. Though OWTs are relatively less sensitive to earthquakes than typical structures, liquefaction of soil surrounding monopiles may have serious implications on the dynamic performance of the system. During liquefaction there is a loss of support along the depth of the monopile which noticeably reduces the stiffness of the system. This results in a decrease of the fundamental frequency and may cause resonating effects with high energy wave loads up until liquefaction effects are reduced with time. Therefore, these resonating effects will increase the fatigue damage and/or the overall accumulated rotation of the structure. Therefore, in this paper, the effect of liquefaction on the natural frequency of OWTs was considered through a parametric study which considers various soil conditions, liquefaction depths (DL), monopile diameters (D) and monopile lengths (LP). The finite element method used in this parametric study was validated via an analytical solution available in literature and a large-scale experiment which considers a fixed base condition. The study shows that the change in the natural frequency under various liquefaction depths is not significantly influenced by monopile diameter when the length is kept constant. On the other hand, the monopile length has a more detrimental effect and the aspect ratio is that LP/D is a significant non-dimensional term governing dynamic behaviour of OWT systems in the case of liquefaction. In addition, it is shown that the overall results are more sensitive in looser soils and special design considerations are provided for different ground conditions. Finally, based on analytical solutions provided in literature, a simplified method is presented to estimate the change of the natural frequency taking into account the liquefaction depth which can be easily programmed in a spreadsheet type program followed by a step-by-step solved example which also serves the purpose of verification and validation. [ABSTRACT FROM AUTHOR]

Background: Cancer-related fatigue is a serious side effect of cancer, and its treatment can disrupt the quality of life of patients. Clinically, the standard method for assessing cancer-related fatigue relies on subjective experience retrieved from patient self-reports, such as the Brief Fatigue Inventory (BFI). However, most patients do not self-report their fatigue levels.Objective: In this study, we aim to develop an objective cancer-related fatigue assessment method to track and monitor fatigue in patients with cancer.Methods: In total, 12 patients with lung cancer who were undergoing chemotherapy or targeted therapy were enrolled. We developed frequency-domain parameters of heart rate variability (HRV) and BFI based on a wearable-based HRV measurement system. All patients completed the BFI-Taiwan version questionnaire and wore the device for 7 consecutive days to record HRV parameters such as low frequency (LF), high frequency (HF), and LF-HF ratio (LF-HF). Statistical analysis was used to map the correlation between subjective fatigue and objective data.Results: A moderate positive correlation was observed between the average LF-HF ratio and BFI in the sleep phase (ρ=0.86). The mapped BFI score derived by the BFI mapping method could approximate the BFI from the patient self-report. The mean absolute error rate between the subjective and objective BFI scores was 3%.Conclusions: LF-HF is highly correlated with the cancer-related fatigue experienced by patients with lung cancer undergoing chemotherapy or targeted therapy. Beyond revealing fatigue levels objectively, continuous HRV recordings through the photoplethysmography watch device and the defined parameters (LF-HF) can define the active phase and sleep phase in patients with lung cancer who undergo chemotherapy or targeted chemotherapy, allowing a deduction of their sleep patterns. [ABSTRACT FROM AUTHOR]