47 research outputs found
An experimental study on the lateral pile–soil interaction of offshore tetrapod piled jacket foundations in sand
No full textRecently, tetrapod piled jacket (TPJ) foundations have shown considerable promise in offshore developments, due to the increases in power capacity and water depth for offshore wind turbines. This paper presents a set of centrifuge tests to look into the lateral loading behaviour of TPJ foundations in sand, with the overall load–displacement responses of the foundation as well as the soil resistance and internal forces on or within individual piles being examined carefully. Test results show that the back-row piles are more likely to be pulled out when the TPJ foundation is loaded laterally along the diagonal direction compared to when loaded along the orthogonal direction. The lateral soil resistance per unit length on the back-row pile(s) is approximately 60% of that on the front-row one(s) in the orthogonal loading case, and only about 40% in the diagonal loading case. Moreover, although the TPJ foundation is in its form a special case of pile groups, it is highlighted in the present study that the former case exhibits distinct loading behaviour from the latter case due to the typically large overturning moment encountered by the foundations for offshore wind turbines. Finally, the p-multipliers of the piles are demonstrated to be dependent on pile deflections, but independent on soil depths, and as a result, a modified pm model is proposed to provide guidance for the design of TPJ foundations in sand.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author
Part-Whole Relational Few-Shot 3D Point Cloud Semantic Segmentation
No full textThe author wishes to extend sincere appreciation to Professor Lin Shi for the generous provision of equipment support, which significantly aided in the successful completion of this research. Furthermore, the author expresses gratitude to Associate Professor Ning Li and Teacher Wei Guan for their invaluable academic guidance and unwavering support. Their expertise and advice played a crucial role in shaping the direction and quality of this research.Peer reviewe
LC-MS/MS Method for Simultaneous Quantification of Dexmedetomidine, Dezocine, and Midazolam in Rat Plasma and Its Application to Their Pharmacokinetic Study
No full textA simple, sensitive, and accurate LC-MS/MS method was established and validated for the simultaneous quantification of dexmedetomidine, dezocine, and midazolam in rat plasma. Chromatographic separation was achieved on a C18 column (50 mm × 2.1 mm, 3 µm) using a mobile phase composed of water (containing 0.1% formic acid) and acetonitrile. The lower limits of quantification were 0.1, 0.1, and 0.2 ng/mL for dexmedetomidine, dezocine, and midazolam in rat plasma, respectively. The analytes were determined with selected reaction monitoring under positive ionization mode. The intra- and interday precision and accuracy were all within acceptable limits during the entire validation, and the stability of analytes was acceptable under various storage conditions. The validated method was successfully applied in pharmacokinetic studies of dexmedetomidine, dezocine, and midazolam following intravenous injection
Effects of Laser Cladding Layers Width on Total Indicated Runout Characteristics of Steam Turbine Rotor Surface
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Fish Detection Using Deep Learning
No full textRecently, human being’s curiosity has been expanded from the land to the sky and the sea. Besides sending people to explore the ocean and outer space, robots are designed for some tasks dangerous for living creatures. Take the ocean exploration for an example. There are many projects or competitions on the design of Autonomous Underwater Vehicle (AUV) which attracted many interests. Authors of this article have learned the necessity of platform upgrade from a previous AUV design project, and would like to share the experience of one task extension in the area of fish detection. Because most of the embedded systems have been improved by fast growing computing and sensing technologies, which makes them possible to incorporate more and more complicated algorithms. In an AUV, after acquiring surrounding information from sensors, how to perceive and analyse corresponding information for better judgement is one of the challenges. The processing procedure can mimic human being’s learning routines. An advanced system with more computing power can facilitate deep learning feature, which exploit many neural network algorithms to simulate human brains. In this paper, a convolutional neural network (CNN) based fish detection method was proposed. The training data set was collected from the Gulf of Mexico by a digital camera. To fit into this unique need, three optimization approaches were applied to the CNN: data augmentation, network simplification, and training process speed up. Data augmentation transformation provided more learning samples; the network was simplified to accommodate the artificial neural network; the training process speed up is introduced to make the training process more time efficient. Experimental results showed that the proposed model is promising, and has the potential to be extended to other underwear objects
