Dynamic Analysis of a 10 MW Floating Offshore Wind Turbine Considering the Tower and Platform Flexibility

Recently,semisubmersible floating offshore wind turbine technologies have received considerable attention.For the coupled simulation of semisubmersible floating offshore wind energy,the platform is usually considered a rigid model,which could affect the calculation accuracy of the dynamic responses.The dynamic responses of a TripleSpar floating offshore wind turbine equipped with a 10 MW offshore wind turbine are discussed herein.The simulation of a floating offshore wind turbine under regular waves,white noise waves,and combined wind-wave conditions is conducted.The effects of the tower and platform flexibility on the motion and force responses of the TripleSpar semisubmersible floating offshore wind turbine are investigated.The results show that the flexibility of the tower and platform can influence the dynamic responses of a TripleSpar semisubmersible floating offshore wind turbine.Considering the flexibility of the tower and platform,the tower and platform pitch motions markedly increased compared with the fully rigid model.Moreover,the force responses,particularly for tower base loads,are considerably influenced by the flexibility of the tower and platform.Thus,the flexibility of the tower and platform for the coupled simulation of floating offshore wind turbines must be appropriately examined.

Renewable Biomass as a Platform for Preparing Green Chemistry

1 About the Special Issue Editor Qiaoguang Li is an associate professor and master’s supervisor in the Department of College of Chemistry and Chemical Engineering,Zhongkai University of Agriculture and Engineering.He received his PhD from Institute of Chemical Industry of Forestry Products,Chinese Academy of Forestry in 2018.He has been focusing his research on the chemical basis and application of natural resources.He has published nearly 30 international peer reviewed papers and applied for 10 patents.

Dynamic Coupling Analysis of Semisubmersible Platform Float-over Method for Docking Case

In this paper,the multi-body coupled dynamic characteristics of a semisubmersible platform and an HYSY 229 barge were investigated.First,coupled hydrodynamic analysis of the HYSY 229 barge and the semisubmersible platform was performed.Relevant hydrodynamic parameters were obtained using the retardation function method of three-dimensional frequency-domain potential flow theory.The results of the hydrodynamic analysis were highly consistent with the test findings,verifying the accuracy of the multifloating hydrodynamic coupling analysis,and key hydrodynamic parameters were solved for different water depths and the coupling effect.According to the obtained results,the hydrodynamic influence was the largest in shallow waters when the coupling effect was considered.Furthermore,the coupled motion equation combined with viscous damping,fender system,and mooring system was established,and the hydrodynamics,floating body motion,and dynamic response of the fender system were analyzed.Motion analysis revealed good agreement among the surge,sway,and yaw motions of the two floating bodies.However,when the wave period reached 10 s,the motion of the two floating bodies showed severe shock,and a relative motion was also observed.Therefore,excessive constraints should be added between the two floating bodies during construction to ensure construction safety.The numerical analysis and model test results of the semisubmersible platform and HYSY 229 barge at a water depth of 42 m and sea conditions of 0°,45°,and 90° were in good agreement,and the error was less than 5%.The maximum movement of the HYSY 229 barge reached 2.61 m in the sway direction,whereas that of the semisubmersible platform was 2.11 m.During construction,excessive constraints should be added between the two floating bodies to limit their relative movement and ensure construction safety.

Application of GNSS-PPP on Dynamic Deformation Monitoring of Offshore Platforms

The real-time dynamic deformation monitoring of offshore platforms under environmental excitation is crucial to their safe operation.Although Global Navigation Satellite System-Precise Point Positioning(GNSS-PPP)has been considered for this purpose,its monitoring accuracy is relatively low.Moreover,the influence of background noise on the dynamic monitoring accuracy of GNSS-PPP remains unclear.Hence,it is imperative to further validate the feasibility of GNSS-PPP for deformation monitoring of offshore platforms.To address these concerns,vibration table tests with different amplitudes and frequencies are conducted.The results demonstrate that GNSS-PPP can effectively monitor horizontal vibration displacement as low as±30 mm,which is consistent with GNSS-RTK.Furthermore,the spectral characteristic of background noise in GNSS-PPP is similar to that of GNSS-RTK(Real Time Kinematic).Building on this observation,an improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)has been proposed to de-noise the data and enhance the dynamic monitoring accuracy of GNSS-PPP.Field monitoring application research is also undertaken,successfully extracting and analyzing the dynamic deformation of an offshore platform structure under environmental excitation using GNSS-PPP monitoring in conjunction with improved CEEMDAN de-noising.By comparing the de-noised dynamic deformation trajectories of the offshore platform during different periods,it is observed that the platform exhibits reversible alternating vibration responses under environmental excitation,with more pronounced displacement deformation in the direction of load action.The research results confirm the feasibility and potential of GNSS-PPP for dynamic deformation monitoring of offshore platforms.

Quantum circuit-based proxy blind signatures:A novel approach and experimental evaluation on the IBM quantum cloud platform

This paper presents a novel approach to proxy blind signatures in the realm of quantum circuits,aiming to enhance security while safeguarding sensitive information.The main objective of this research is to introduce a quantum proxy blind signature(QPBS)protocol that utilizes quantum logical gates and quantum measurement techniques.The QPBS protocol is constructed by the initial phase,proximal blinding message phase,remote authorization and signature phase,remote validation,and de-blinding phase.This innovative design ensures a secure mechanism for signing documents without revealing the content to the proxy signer,providing practical security authentication in a quantum environment under the assumption that the CNOT gates are securely implemented.Unlike existing approaches,our proposed QPBS protocol eliminates the need for quantum entanglement preparation,thus simplifying the implementation process.To assess the effectiveness and robustness of the QPBS protocol,we conduct comprehensive simulation studies in both ideal and noisy quantum environments on the IBM quantum cloud platform.The results demonstrate the superior performance of the QPBS algorithm,highlighting its resilience against repudiation and forgeability,which are key security concerns in the realm of proxy blind signatures.Furthermore,we have established authentic security thresholds(82.102%)in the presence of real noise,thereby emphasizing the practicality of our proposed solution.

Research on the Legal Framework of Content Regulations for Network Platforms

In the era of the Internet,various network platforms have evolved into new hubs for information dissemination.Currently,China has established a platform-centered content regulation framework,wherein platforms proactively enforce content regulations in accordance with legal censorship obligations.Additionally,platform policies and user agreements augment their authority in content regulation.The platforms can achieve cost-effective and highly efficient content regulation by leveraging their strategic advantages enabled by their own technical capabilities and extensive coverage.The platform self-regulation model,however,still faces challenges.First,accurately evaluating content remains a formidable task;second,ensuring effective platform publicity through self-regulation poses difficulties;third,users may potentially face disadvantages due to the platform’s right of self-regulation;and fourth,digital copyright owners face challenges when defending digital copyright disputes under the safe harbor rule.Therefore,it is imperative to establish,review,and revise the legal framework for content regulation of network platforms in order to enhance the efficiency of their governance systems.The formulation of the legal framework for content regulation of network platforms may encompass the following aspects:rationalizing obligations pertaining to platform content regulations,enhancing supervision over platform self-regulation,and establishing a dual-track responsibility system for digital copyright content regulation.This will ensure a harmonious balance among public interests,users’personal rights and interests,and commercial benefits through regulating the content on network platforms.

Research on the Audio Publishing of Classical Books Based on the Theory of Business Model Canvas: Taking Romance of the Three Kingdoms in Digital Audio Platforms as an Example

Visual media have dominated sensory communications for decades,and the resulting“visual hegemony”leads to the call for the“auditory return”in order to achieve a holistic balance in cultural acceptance.Romance of the Three Kingdoms,a classic literary work in China,has received significant attention and promotion from leading audio platforms.However,the commercialization of digital audio publishing faces unprecedented challenges due to the mismatch between the dissemination of long-form content on digital audio platforms and the current trend of short and fast information reception.Drawing on the Business Model Canvas Theory and taking Romance of the Three Kingdoms as the main focus of analysis,this paper argues that the construction of a business model for the audio publishing of classical books should start from three aspects:the user evaluation of digital audio platforms,the establishment of value propositions based on the“creative transformation and innovative development”principle,and the improvement of the audio publishing infrastructure to ensure the healthy operation and development of the digital audio platforms and consequently improve their current state of development and expand the boundaries of cultural heritage.

Transforming Digital Experiences: The Evolution of Digital Experience Platforms (DXPs) from Monoliths to Microservices: A Practical Guide

The research aims to explore the transition from monolithic Digital Experience Platforms (DXPs) to Microservices-based DXPs, addressing scalability challenges. The study systematically decomposes monolithic structures into Microservices, emphasizing business capability and subdomain decomposition. Concrete insights, challenges, and solutions encountered during this transformation process are presented. The research contributes valuable insights into the challenges and benefits of adopting Microservices in DXPs. Results highlight the importance of architectural patterns and strategic scaling dimensions for improved performance and scalability. The case study on Backbase’s Engagement Banking Platform showcases successful implementation, providing flexibility, integration, and efficient development in the evolving DXP landscape.

Research on the Design and Application of Virtual and Real Integrated Training Platform Based on Intelligent Manufacturing

In this paper,we built a robot training platform using virtual simulation software,and the robot assembly,handling,and palletizing were realized.The workstation includes an industrial robot,gas control unit,track function module,assembly function module,palletizing function module,vision module,etc.,and robot movement is achieved through language programming.The platform provides conditions for the practical ability training of application-oriented talents.

Research on Network Security Level Protection Measurement Strategy in the Context of Cloud Platforms

Platforms facilitate information exchange,streamline resources,and reduce production and management costs for companies.However,some viral information may invade and steal company resources,or lead to information leakage.For this reason,this paper discusses the standards for cybersecurity protection,examines the current state of cybersecurity management and the risks faced by cloud platforms,expands the time and space for training on cloud platforms,and provides recommendations for measuring the level of cybersecurity protection within cloud platforms in order to build a solid foundation for them.

Application Effect of Blended Education Strategy Based on the Learning Pass Platform in Phase III Cardiac Rehabilitation of Patients with Coronary Artery Disease

Objective:To explore the application effect of the blended education strategy based on the Learning Pass platform in the phase III cardiac rehabilitation of patients with coronary artery disease.Methods:90 patients diagnosed with coronary artery disease in the Department of Cardiology of our hospital from January 2019 to January 2021 were selected and divided into the control group and the experimental group according to the method of randomized numerical table,with 45 cases in each group.Both the experimental group and the control group received pre-discharge cardiac rehabilitation education by conventional means.The control group received education and supervision information via WeChat after discharge,while the experimental group joined the Learning Pass platform to receive online and offline hybrid education and supervision,with online as the mainstay and offline as a supplement.The disease cognitive level,self-management skills,quality of life,medication adherence,and emotional status of the two groups were compared.Results:The disease cognitive levels in the experimental group were significantly higher than those of the control group(P<0.05);the scores of the experimental group in terms of quality of life,self-management skills,and medication adherence were significantly higher than those of the control group(P<0.05);and the scores of anxiety and depression in the experimental group were significantly lower than those of the control group(P<0.05).Conclusion:The blended education strategy based on the Learning Pass platform has a significant application effect in phase III cardiac rehabilitation of patients with coronary artery disease.It can improve patients’disease cognitive level,self-management skills,and quality of life,and provide a basis for improving patients’prognosis.

Structural Design Study of Air-Dropped Unmanned Maritime Mobile Search and Rescue Platforms

In order to improve the efficiency and safety of search and rescue(SAR)at sea,this paper proposes a kind of emergency rapid rescue unmanned craft(air-dropped unmanned maritime motorized search and rescue platform)that can be delivered by a large transport aircraft.This paper studies the structural design scheme of the platform,and the main scale of the platform,the choice of power system and the impact resistance performance are considered in the design process to ensure its rapid response and effective rescue capability under complex sea conditions.Simulation results show that the platform can withstand the impact of air injection into the water and the shipboard equipment can operate normally under the impact load,thus verifying the feasibility and safety of the design.This study serves to improve the maritime search and rescue system and enhance the oceanic emergency response capability.

Self-Learning and Its Application to Laminar Cooling Model of Hot Rolled Strip

The mathematical model for online controlling hot rolled steel cooling on run-out table （ROT for abbreviation） was analyzed, and water cooling is found to be the main cooling mode for hot rolled steel. The calculation of the drop in strip temperature by both water cooling and air cooling is summed up to obtain the change of heat transfer coefficient. It is found that the learning coefficient of heat transfer coefficient is the kernel coefficient of coiler temperature control （CTC） model tuning. To decrease the deviation between the calculated steel temperature and the measured one at coiler entrance, a laminar cooling control self-learning strategy is used. Using the data acquired in the field, the results of the self-learning model used in the field were analyzed. The analyzed results show that the self-learning function is effective.

Self-Learning of Multivariate Time Series Using Perceptually Important Points

In machine learning,positive-unlabelled(PU)learning is a special case within semi-supervised learning.In positiveunlabelled learning,the training set contains some positive examples and a set of unlabelled examples from both the positive and negative classes.Positive-unlabelled learning has gained attention in many domains,especially in time-series data,in which the obtainment of labelled data is challenging.Examples which originate from the negative class are especially difficult to acquire.Self-learning is a semi-supervised method capable of PU learning in time-series data.In the self-learning approach,observations are individually added from the unlabelled data into the positive class until a stopping criterion is reached.The model is retrained after each addition with the existent labels.The main problem in self-learning is to know when to stop the learning.There are multiple,different stopping criteria in the literature,but they tend to be inaccurate or challenging to apply.This publication proposes a novel stopping criterion,which is called Peak evaluation using perceptually important points,to address this problem for time-series data.Peak evaluation using perceptually important points is exceptional,as it does not have tunable hyperparameters,which makes it easily applicable to an unsupervised setting.Simultaneously,it is flexible as it does not make any assumptions on the balance of the dataset between the positive and the negative class.

Development of a target capture sequencing SNP genotyping platform for genetic analysis and genomic breeding in rapeseed

Rapeseed(Brassica napus)is an oil crop grown worldwide,making it a key plant species in molecular breeding research.However,the complexity of its polyploid genome increases sequencing costs and reduces sequencing accuracy.Target capture coupled with high-throughput sequencing is an efficient approach for detecting genetic variation at genomic regions or loci of interest.In this study,588 resequenced accessions of rapeseed were used to develop a target capture sequencing SNP genotyping platform named BnaPan50T.The platform comprised 54,765,with 54,058 resequenced markers from the pan-genome,and 855 variant trait-associated markers for 12 agronomic traits.The capture quality of BnaPan50T was demonstrated well in 12 typical accessions.Compared with a conventional genotyping array,BnaPan50T has a high SNP density and a high proportion of SNPs in unique physical positions and in annotated functional genes,promising wide application.Target capture sequencing and wholegenome resequencing in 90 doubled-haploid lines yielded 60%specificity,78%uniformity within tenfold coverage range,and 93%genotyping accuracy for the platform.BnaPan50T was used to construct a genetic map for quantitative trait loci(QTL)mapping,identify 21 unique QTL,and predict several candidate genes for yield-related traits in multiple environments.A set of 132 core SNP loci was selected from BnaPan50T to construct DNA fingerprints and germplasm identification resources.This study provides genomics resources to support target capture sequencing,genetic analysis and genomic breeding of rapeseed.

Where Have Network-based Self-learning Classes Gone?——Reflections & Expectations on the Employment of Network-based Self-learning Classes

To respond to the further development of college English reforms,many universities employed network-based selflearning classes to aid the traditional classroom teaching,especially in teaching listening,but as time went by,some universities gradually gave them up.The paper intends to reflect on the employment of network-based self-learning listening classes,analyz ing the learning with and without its aid,and meanwhile introduce the need to re-employ it,and discuss how we can improve the network-based self-learning classes to help with students' listening.

SELF-LEARNING FUZZY CONTROL RULES USING GENETIC ALGORITHMS

This papcr presents a new genetic algorithms(GAs)-based method for self-learniag fuzzy control rules. An improved GA is used to learn to optimally select the fuzzy membership functions of the linguistic labels in the condition portion of each rule, and to automatically generate fuzzy control actions under each condition. The dynamics of the controlled system is unknown to the GA. The only information for evaluating performance is a failure signal indicating that the controlled system is out of control. We compare its performance with that of other learning methods for the same problem. We also examine the ability of the algorithm to adapt to changing conditions. Simulation results show that such an approach for self-learning fuzzy control rules is both effective and robust.

Structural features and exploration targets of platform margins in Sinian Dengying Formation in Deyang-Anyue Rift, Sichuan Basin, SW China

Based on the seismic, logging, drilling and other data, the distribution, structural types and mound-shoal hydrocarbon accumulation characteristics of platform margins of the Sinian Dengying Formation in the Deyang-Anyue Rift and its periphery were analyzed. Four types of platform margins are developed in the Dengying Formation, i.e., single-stage fault-controlled platform margin, multi-stage fault-controlled platform margin, gentle slope platform margin, and overlapping platform margin. In the Gaoshiti West-Weiyuan East area, single-stage fault controlled platform margins are developed in the Deng 2 Member, which trend in nearly NEE direction and are shielded by faults and mudstones, forming fault-controlled–lithologic traps. In the Lezhi-Penglai area, independent and multi-stage fault controlled platform margins are developed in the Deng 2 Member, which trend in NE direction and are controlled by synsedimentary faults;the mound-shoal complexes are aggraded and built on the hanging walls of the faults, and they are shielded by tight intertidal belts and the Lower Cambrian source rocks in multiple directions, forming fault-controlled–lithologic and other composite traps. In the Weiyuan-Ziyang area, gentle slope platform margins are developed in the Deng 2 Member, which trend in NW direction;the mound-shoal complexes are mostly thin interbeds as continuous bands and shielded by tight intertidal belts in the updip direction, forming lithologic traps. In the Gaoshiti-Moxi-Yanting area, overlapping platform margins are developed in the Deng 2 and Deng 4 members;the mound-shoal complexes are aggraded and overlaid to create platform margin buildup with a huge thickness and sealed by tight intertidal belts and the Lower Cambrian mudstones in the updip direction, forming large-scale lithologic traps on the north slope of the Central Sichuan Paleouplift. To summarize, the mound-shoal complexes on the platform margins in the Dengying Formation in the Penglai-Zhongjiang area, Moxi North-Yanting area and Weiyuan-Ziyang area are large in scale, with estimated resources of 1.58×1012 m3, and they will be the key targets for the future exploration of the Dengying Formation in the Sichuan Basin.

Mathematical model for cooling process and its self-learning applied in hot rolling mill

Control precision of coiling temperature is one of the key factors affecting the profile shape and surface quality during the cooling process of hot rolled steel strip.For this reason,the core of temperature control precision is to establish an effective cooling mathematical model with self-learning function.Starting from this point,a cooling mathematical model with nonlinear structural characteristics is established in this paper for the cooling process of hot rolled steel strip.By the analysis of self-learning ability,key parameters of the mathematical model could be constantly corrected so as to improve temperature control precision and adaptive capability of the model.The site actual application results proved the stable performance and high control precision of the proposed mathematical model,which would lay a solid foundation to improve the steel product qualities.

Thalassemia Screening by Sentiment Analysis on Social Media Platform Twitter

Thalassemia syndrome is a genetic blood disorder induced by the reduction of normal hemoglobin production,resulting in a drop in the size of red blood cells.In severe forms,it can lead to death.This genetic disorder has posed a major burden on public health wherein patients with severe thalassemia need periodic therapy of iron chelation and blood transfusion for survival.Therefore,controlling thalassemia is extremely important and is made by promoting screening to the general population,particularly among thalassemia carriers.Today Twitter is one of the most influential social media platforms for sharing opinions and discussing different topics like people’s health conditions and major public health affairs.Exploring individuals’sentiments in these tweets helps the research centers to formulate strategies to promote thalassemia screening to the public.An effective Lexiconbased approach has been introduced in this study by highlighting a classifier called valence aware dictionary for sentiment reasoning(VADER).In this study applied twitter intelligence tool(TWINT),Natural Language Toolkit(NLTK),and VADER constitute the three main tools.VADER represents a gold-standard sentiment lexicon,which is basically tailored to attitudes that are communicated by using social media.The contribution of this study is to introduce an effective Lexicon-based approach by highlighting a classifier calledVADERto analyze the sentiment of the general population,particularly among thalassemia carriers on the social media platform Twitter.In this study,the results showed that the proposed approach achieved 0.829,0.816,and 0.818 regarding precision,recall,together with F-score,respectively.The tweets were crawled using the search keywords,“thalassemia screening,”thalassemia test,“and thalassemia diagnosis”.Finally,results showed that India and Pakistan ranked the highest in mentions in tweets by the public’s conversations on thalassemia screening with 181 and 164 tweets,respectively.