Novel deconvolution method for extreme FPSO vessel hawser tensions during offloading operations

Robust prediction of extreme hawser tensions during Floating Production Storage and Offloading (FPSO) operations is an important safety and reliability concern. Excessive hawser tension may occur during certain environmental conditions, posing an operational risk. The novel deconvolution method is proposed in this paper to provide an accurate extreme value prediction. The predicted return level values produced by the new deconvolution approach are compared with those obtained by the Naess-Gaidai method. On the basis of the suggested approach's overall performance, it is concluded that the innovative deconvolution method may give a more robust and accurate forecast of excessive hawser stress. The stated method may be used effectively at the stage of vessel design while determining appropriate vessel characteristics to reduce possible FPSO hawser stress.publishedVersio

A novel multi-dimensional reliability approach for floating wind turbines under power production conditions

Floating offshore wind turbines (FOWT) generate green renewable energy and are a vital part of the modern offshore wind energy industry. Robust predicting extreme offshore loads during FOWT operations is an important safety concern. Excessive structural bending moments may occur during certain sea conditions, posing an operational risk of structural damage. This paper uses the FAST code to analyze offshore wind turbine structural loads due to environmental loads acting on a specific FOWT under actual local environmental conditions. The work proposes a unique Gaidai-Fu-Xing structural reliability approach that is probably best suited for multi-dimensional structural responses that have been simulated or measured over a long period to produce relatively large ergodic time series. In the context of numerical simulation, unlike existing reliability approaches, the novel methodology does not need to re-start simulation again each time the system fails. As shown in this work, an accurate forecast of the probability of system failure can be made using measured structural response. Furthermore, traditional reliability techniques cannot effectively deal with large dimensionality systems and cross-correction across multiple dimensions. The paper aims to establish a state-of-the-art method for extracting essential information concerning extreme responses of the FOWT through simulated time-history data. Three key components of structural loads are analyzed, including the blade-root out-of-plane bending moment, tower fore-aft bending moment, and mooring line tension. The approach suggested in this study allows predicting failure probability efficiently for a non-linear multi-dimensional dynamic system as a whole.publishedVersio

Identification of Balanced Chromosomal Rearrangements Previously Unknown Among Participants in the 1000 Genomes Project: Implications for Interpretation of Structural Variation in Genomes and the Future of Clinical Cytogenetics

Purpose Recent studies demonstrate that whole-genome sequencing (WGS) enables detection of cryptic rearrangements in apparently balanced chromosomal rearrangements (also known as balanced chromosomal abnormalities, BCAs) previously identified by conventional cytogenetic methods. We aimed to assess our analytical tool for detecting BCAs in The 1000 Genomes Project without knowing affected bands. Methods: The 1000 Genomes Project provides an unprecedented integrated map of structural variants in phenotypically normal subjects, but there is no information on potential inclusion of subjects with apparently BCAs akin to those traditionally detected in diagnostic cytogenetics laboratories. We applied our analytical tool to 1,166 genomes from the 1000 Genomes Project with sufficient physical coverage (8.25-fold). Results: Our approach detected four reciprocal balanced translocations and four inversions ranging in size from 57.9 kb to 13.3 Mb, all of which were confirmed by cytogenetic methods and PCR studies. One of DNAs has a subtle translocation that is not readily identified by chromosome analysis due to similar banding patterns and size of exchanged segments, and another results in disruption of all transcripts of an OMIM gene. Conclusions: Our study demonstrates the extension of utilizing low-coverage WGS for unbiased detection of BCAs including translocations and inversions previously unknown in the 1000 Genomes Project