Propagation Properties of Shock Waves in Polyurethane Foam based on Atomistic Simulations

Porous materials are widely used in the field of protection because of their excellent energy absorption characteristics.In this work,a series of polyurethane microscopic models are established and the effect of porosity on the shock waves is studied with classical molecular dynamics simulations.Firstly,shock Hugoniot relations for different porosities are obtained,which compare well with the experimental data.The pores collapse and form local stress wave,which results in the complex multi-wave structure of the shock wave.The microstructure analysis shows that the local stress increases and the local velocity decreases gradually during the process of pore collapse to complete compaction.Finally,it leads to stress relaxation and velocity homogenization.The shock stress peaks can be fitted with two exponential functions,and the amplitude of attenuation coefficient decreases with the increase of density.Besides,the pore collapse under shock or non-shock are discussed by the entropy increase rate of the system.The energy is dissipated mainly through the multiple interactions of the waves under shock.The energy is dissipated mainly by the friction between atoms under non-shock.

Review of Experimental-Numerical Methodologies and Challenges for Floating Offshore Wind Turbines

Due to the dissimilar scaling issues,the conventional experimental method of FOWTs can hardly be used directly to validate the full-scale global dynamic responses accurately.Therefore,it is of absolute necessity to find a more accurate,economic and efficient approach,which can be utilized to predict the full-scale global dynamic responses of FOWTs.In this paper,a literature review of experimental-numerical methodologies and challenges for FOWTs is made.Several key challenges in the conventional basin experiment issues are discussed,including scaling issues;coupling effects between aero-hydro and structural dynamic responses;blade pitch control strategies;experimental facilities and calibration methods.Several basin experiments,industrial projects and numerical codes are summarized to demonstrate the progress of hybrid experimental methods.Besides,time delay in hardware-in-the-loop challenges is concluded to emphasize their significant role in real-time hybrid approaches.It is of great use to comprehend these methodologies and challenges,which can help some future researchers to make a footstone for proposing a more efficient and functional hybrid basin experimental and numerical method.

A two‐branch network with pyramid‐based local and spatial attention global feature learning for vehicle re‐identification

In recent years,vehicle re‐identification has attracted more and more attention.How to learn the discriminative information from multi‐view vehicle images becomes one of the challenging problems in vehicle re‐identification field.For example,when the viewpoint of the image changes,the features extracted from one image may be lost in another image.A two‐branch network with pyramid‐based local and spatial attention global feature learning(PSA)is proposed for vehicle re‐identification to solve this issue.Specifically,one branch learns local features at different scales by building pyramid from coarse to fine and the other branch learns attentive global features by using spatial attention module.Subsequently,pooling operation by using global maximum pooling(GMP)for local features and global average pooling(GAP)for global feature is performed.Finally,local feature vectors and global feature vector extracted from the last pooling layer,respectively,are employed for identity re‐identification.The experimental results demonstrate that the proposed method achieves state‐of‐the‐art results on the VeRi‐776 dataset and VehicleID dataset.

Health economic evaluation on population-based Helicobacter pylori eradication and endoscopic screening for gastric cancer prevention

Gastric cancer is a global public health burden, nearly one million new cases are diagnosed per year worldwide, of which 44% of cases occur in China. The prognosis of gastric cancer varies remarkably by the stage of cancer, and most of the patients in China are diagnosed at advanced stages, resulting in poor prognoses. Effective strategies to reduce the burden of gastric cancer include primary prevention through testing and treatment of Helicobacter pylori(H. pylori) and secondary prevention by screening and early detection. Although many countries have issued management guidelines and consensus reports concerning these strategies, the limited availability of healthcare resources often precludes their widespread implementation. Therefore, assessing the costs, benefits, and harms of population-based intervention measures through health economic evaluation is necessary for informed health policy decisions. Accordingly, we synthesize management approaches from different countries on H. pylori eradication and endoscopic screening, and also summarize recent advancements in health economic evaluations on population-based preventive strategies. The goal of the review is to provide empirical evidence supporting optimal resource allocation, maximizing benefits for the population, and ultimately reducing the burden of gastric cancer.

A Bi-layer Composite Film Based on TiO_2 Hollow Spheres, P25,and Multi-walled Carbon Nanotubes for Efficient Photoanode of Dye-sensitized Solar Cell

A bi-layer photoanode for dye-sensitized solar cell(DSSC) was fabricated, in which TiO_2 hollow spheres(THSs) were designed as a scattering layer and P25/multi-walled carbon nanotubes(MWNTs) as an under-layer. The THSs were synthesized by a sacrifice template method and showed good light scattering ability as an over-layer of the photoanode. MWNTs were mixed with P25 to form an under-layer of the photoanode to improve the electron transmission ability of the photoanode. The power conversion efficiency of this kind of DSSC with bi-layer was enhanced to 5.13 %,which is 14.25 % higher than that of pure P25 DSSC.Graphical Abstract A bi-layer composite photoanode based on P25/MWNTs-THSs with improved light scattering and electron transmission, which will provide a new insight into fabrication and structure design of highly efficient dyesensitized solar cells.

Critical Void Volume Fraction Identification Based on Mesoscopic Damage Model for NVA Shipbuilding Steel

NVA mild steel is a commonly used material in the shipbuilding industry.An accurate model for description of this material’s ductile fracture behaviour in numerical simulation is still a challenging task.In this paper,a new method for predicting the critical void volume fraction fc in the Guson-Tvergaard-Needleman(GTN)model is introduced to describe the ductile fracture behaviour of NVA shipbuilding mild steel during ship collision and grounding scenarios.Most of the previous methods for determination of the parameter fc use a converse method,which determines the values of the parameters through comparisons between experi-mental results and numerical simulation results but with high uncertainty.A new method is proposed based on the Hill,Bressan,and Williams hypothesis,which reduces the uncertainty to a satisfying extent.To accurately describe the stress-strain relationship of materials before and after necking,a combination of the Voce and Swift models is used to describe the material properties of NVA mild steel.A user-defined material subroutine has been developed to enable the application of the new parameter deter-mination method and its implementation in the finite element software LS-DYNA.It is observed that the model can accurately describe structural damage by comparing the numerical simulation results with those of experiments;thus,the results demon-strate the model’s capacity for structural response prediction in ship collision and grounding scenario simulations。

Investigation of Heave Response of the Deepwater Octagonal FDPSO Using Various Heave Plate Configurations

Heave plates can be employed to control undesirable heave motion amplitudes of the deepwater octagonal Floating, Drilling, Production, Storage, and Offloading(FDPSO) platform. Numerical simulations and model tests were applied to analyze and investigate the hydrodynamic response and the feasibility of the heave plate configurations. The diameter and the depth below the free surface of a single-layer heave plate, as well as the spacing of two-layer heave plates, were considered as the primary variables when studying the effect of heave plates on FDPSO hydrodynamics. The analysis results indicate that the heave plate diameter significantly affects the heave hydrodynamics, and heave performance could be improved with an increased diameter. In addition, increasing the depth below the free surface of a single-layer heave plate does not effectively suppress the heave motion within the range of draft depths tested. The target FDPSO obtained better heave characteristics with increased spacing between the two-layer heave plates. Furthermore, the global performances of the octagonal FDPSO with these typical heave plate configurations were comparatively analyzed. The results indicate that from a hydrodynamic point of view, the single-layer heave plate configuration has an advantage over the two-layer heave plate configuration.

Time-Domain Analysis of the Relative Motions Between Side-by-Side FLNG and LNGC Under Oblique Waves

Strong hydrodynamic interactions during the side-by-side offloading operation between floating liquefied natural gas(FLNG) and liquefied natural gas carrier(LNGC) can induce high risks of collision. The weather vane effect of a single-point mooring system normally results in the satisfactory hydrodynamic performance of the side-by-side configuration in head seas. Nevertheless, the changes in wave directions in real sea conditions can significantly influence the relative motions. This article studies the relative motions of the side-by-side system by using the theoretical analysis method and the numerical calculation method. Based on the three-dimensional potential theory modified by artificial damping-lid method, the frequency-domain hydrodynamic coefficients can be improved to calculate the retardation functions for the multi-body problem. An in-house code is then developed to perform the time-domain simulation of two vessels, through which the relative motions are subsequently obtained. A range of oblique waves are chosen for the extensive calculation of relative motions between the two vessels, which are further analyzed in terms of the phase shift of motion responses induced by specific resonant wave patterns. Investigation results show that wave directions have a significant influence on the relative sway, roll, and yaw motions. Under the circumstance that the absolute phase shift between the roll motions of two vessels approaches 180°, stronger relative motions are induced when LNGC is on the weather side.Moreover, the gap water resonances at high frequencies tend to cause the dangerous opposed oscillation of two vessels in the sway and yaw modes, whereas FLNG reduces the gap water resonances and relative motions when located on the weather side.

An Elastic-Plastic Iceberg Material Model Considering Temperature Gradient Effects and its Application to Numerical Study

To simulate the FPSO-iceberg collision process more accurately, an elastic-plastic iceberg material model considering temperature gradient effects is proposed and applied. The model behaves linearly elastic until it reaches the ‘Tsai-Wu’ yield surfaces, which are a series of concentric elliptical curves of different sizes. Decreasing temperature results in a large yield surface. Failure criteria, based on the influence of accumulated plastic strain and hydrostatic pressure, are built into the model. Based on published experimental data on the relationship between depth and temperature in icebergs, three typical iceberg temperature profiles are proposed. According to these, ice elements located at different depths have different temperatures. The model is incorporated into LS-DYNA using a user-defined subroutine and applied to a simulation of FPSO collisions with different types of icebergs. Simulated area-pressure curves are compared with design codes to validate the iceberg model. The influence of iceberg shape and temperature on the collision process is analyzed. It is indicated that FPSO structural damage not only depends on the relative strength between the iceberg and the structure, but also depends on the local shape of the iceberg.

Rapid Prediction of Structural Responses of Double-Bottom Structures in Shoal Grounding Scenario

This study presents a simplified analytical model for predicting the structural responses of double-bottom ships in a shoal grounding scenario. This solution is based on a series of analytical models developed from elastic-plastic mechanism theories for different structural components, including bottom girders, floors, bottom plating, and attached stiffeners. We verify this simplified analytical model by numerical simulation, and establish finite element models for a typical tanker hold and a rigid indenter representing seabed obstacles. Employing the LS-DYNA finite element solver, we conduct numerical simulations for shoal-grounding cases with a wide range of slope angles and indentation depths. In comparison with numerical simulations, we verify the proposed simplified analytical model with respect to the total energy dissipation and the horizontal grounding resistance. We also investigate the interaction effect of deformation patterns between bottom structure components. Our results show that the total energy dissipation and resistances predicted by the analytical model agree well with those from numerical simulations.

A Top-down Method of Extraction Entity Relationship Triples and Obtaining Annotated Data

The extraction of entity relationship triples is very important to build a knowledge graph(KG),meanwhile,various entity relationship extraction algorithms are mostly based on data-driven,especially for the current popular deep learning algorithms.Therefore,obtaining a large number of accurate triples is the key to build a good KG as well as train a good entity relationship extraction algorithm.Because of business requirements,this KG’s application field is determined and the experts’opinions also must be satisfied.Considering these factors we adopt the top-down method which refers to determining the data schema firstly,then filling the specific data according to the schema.The design of data schema is the top-level design of KG,and determining the data schema according to the characteristics of KG is equivalent to determining the scope of data’s collection and the mode of data’s organization.This method is generally suitable for the construction of domain KG.This article proposes a fast and efficient method to extract the topdown type KG’s triples in social media with the help of structured data in the information box on the right side of the related encyclopedia webpage.At the same time,based on the obtained triples,a data labeling method is proposed to obtain sufficiently high-quality training data,using in various Natural Language Processing(NLP)information extraction algorithms’training.

The landscape of gene-CDS-haplotype diversity in rice:Properties,population organization,footprints of domestication and breeding,and implications for genetic improvement

Polymorphisms within gene coding regions represent the most important part of the overall genetic diversity of rice.We characterized the gene-coding sequence-haplotype(gcHap)diversity of 45963 rice genes in 3010 rice accessions.With an average of 226±390 gcHaps per gene in rice populations,rice genes could be classified into three main categories:12865 conserved genes,10254 subspecific differentiating genes,and 22844 remaining genes.We found that 39218 rice genes carry>255179 major gcHaps of potential functional importance.Most(87.5%)of the detected gcHaps were specific to subspecies or populations.The inferred proto-ancestors of local landrace populations reconstructed from conserved predominant(ancient)gcHaps correlated strongly with wild rice accessions from the same geographic regions,supporting a multiorigin(domestication)model of Oryza sativa.Past breeding efforts generally increased the gcHap diversity of modern varieties and'caused significant frequency shifts in predominant gcHaps of 14266 genes due to independent selection in the two subspecies.Low frequencies of“favorable”gcHaps at most known genes related to rice yield in modern varieties suggest huge potential for rice improvement by mining and pyramiding of favorable gcHaps.The gcHap data were demonstrated to have greater power than SNPs for the detection of causal genes that affect complex traits.The rice gcHap diversity dataset generated in this study would facilitate rice basic research and improvement in the future.

Simulation annealing diagnosis algorithm method for optimized forecast of the dynamic response of floating offshore wind turbines

Design of floating offshore wind turbines(FOWTs)needs reliable and innovative technologies to overcome the challenges on how to better predict the dynamic responses in terms of aero-hydro-servo-elastic disciplines.This paper aims to demonstrate the optimized prediction of the dynamic response of FOWTs by Simulation annealing diagnosis algorithm(SADA).SADA is an Artificial Intelligence technology-based method,which utilizes the advantages of numerical simulation,basin experiment and machine learning algorithms.The actor network in deep deterministic policy gradient(DDPG)is adopted to take actions to adjust the Key disciplinary parameters(KDPs)in each loop according to the feedback of 6DOF motions of platform in dynamic response analysis.The results demonstrated that the mean values of the platform's motions and rotor axial thrust force could be predicted with higher accuracy.On this basis,other physical quantities that designers are more concerned about but cannot be obtained from experiments and actual measurements will be predicted by SADA with more credibility.This SADA method differs from traditional supervised learning applications in renewable energy,which do not need to be provided physical quantities with strong direct correlation.All targets can be artificially set for SADA to obtain a better self-learning performance.In general,designers can use SADA to get a more accurate and optimized prediction of the dynamic response of FOWTs,especially those physical quantities that cannot be directly obtained through the basin experiments.

A review of multi-attributes decision-making models for offshore oil and gas facilities decommissioning

With the development of the offshore fossil energy industry,the designing life of many offshore oil and gas facilities will end.The decommissioning of these facilities has become an urgent task due to unpre-dictable costs,high risks,and environmental protection issues of public concern.Decision-making,as the core in the pre-decommissioning stage,plays a decisive role in the cost,risk,and impact of the entire de-commissioning.Therefore,the multi-attribute decision-making model has attracted much attention from industry and academia.An efficient,accurate,and simply using multi-attribute decision-making model can enable governments,energy companies,other marine users,and environmental protection organi-zations to reasonably fulfill their concerns.It is of great significance to all parties.This review mainly studies the multi-attribute decision-making models that have been used in the decommissioning of off-shore oil and gas facilities,and conducts a more detailed interpretation of them,including the relevant regulations,frameworks,methodology,preferences and advantages and disadvantages of different mod-els.In addition,a more comprehensive review of the cost assessment model,an important part of the decision-making model,is carried out,including the general framework and methodology of the cost as-sessment model,and the accuracy of the models is explored.And then the current evaluation method of accuracy of the cost assessment model raises the author’s personal doubts.At the end of the article,this paper names two core problems of the current decision-making model,that is,the lack of basic data and the incomplete MCDA(Multi-criteria Decision Analysis)method.This review can provide a comprehen-sive reference and feasible research directions for future scholars who aims to study the decommissioning of offshore oil and gas facilities especially in the North Sea in the UK and point out the direction for the industry to improve its current multi-attribute decision-making models.

A reined global-local approach for evaluation of singular stress ield based on scaled boundary inite element method

A reined global-local approach based on the scaled boundary inite element method（SBFEM） is proposed to improve the accuracy of predicted singular stress ield. The proposed approach is carried out in conjunction with two steps. First, the entire structure is analyzed by employing an arbitrary numerical method. Then, the interested region, which contains stress singularity, is re-solved using the SBFEM by placing the scaling center right at the singular stress point with the boundary conditions evaluated from the irst step imposed along the whole boundary including the side-faces. Beneiting from the semi-analytical nature of the SBFEM, the singular stress ield can be predicted accurately without highly reined meshes. It provides the FEM or other numerical methods with a rather simple and convenient way to improve the accuracy of stress analysis. Numerical examples validate the effectiveness of the proposed approach in dealing with various kinds of problems.

A mortar contact formulation using scaled boundary isogeometric analysis

Contact analysis is recognized as being the most challenging problem in computational mechanics, because the functional system of contact problems is nonlinear and non-smooth and the convergence and accuracy of contact algorithms are difficult to guarantee. In the traditional finite element method （FEM）-based contact analysis [1,2], the contact body is spatially discretized, and the contact boundary is described using a low-order Lagrange interpolation polynomial. While low-order Lagrange interpolation polynomial works well for planar and low-curvature surfaces [3], artificial oscillations in the contact force and numerical difficulties in the nonlinear solution algorithm occur when a large curvature or finite deformation is encountered [2].

SceGAN:A method for generating autonomous vehicle cut-in scenarios on highways based on deep learning

With the increasing level of automation of autonomous vehicles,it is important to conduct comprehensive and extensive testing before releasing autonomous vehicles into the market.Traditional public road and closed-field testing failed to meet the requirements of high testing efficiency and scenario coverage.Therefore,scenario-based autonomous vehicle simulation testing has emerged.Many scenarios form the basis of simulation testing.Generating additional scenarios from an existing scenario library is a significant problem.Taking the scenarios of a proceeding vehicle cutting into an adjacent lane on highways as an example,based on an autoencoder and a generative adversarial network(GAN),a method that combines Transformer to capture the features of a long-time series,called SceGAN,is proposed to model and generate scenarios of autonomous vehicles on highways.An evaluation system is established to analyze the reliability of SceGAN using discriminative and predictive scores and further evaluate the effect of scenario generation in terms of similarity and coverage.Experiments showed that compared with TimeGAN and AEGAN,SceGAN is superior in data fidelity and availability,and their similarity increased by 27.22%and 21.39%,respectively.The coverage increased from 79.84%to 93.98%as generated scenarios increased from 2,547 to 50,000,indicating that the proposed method has a strong generalization capability for generating multiple trajectories,providing a basis for generating test scenarios and promoting autonomous vehicle testing.