bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of Wave-Induced Motions and Loads of Ships With Forward Speed by Matching Method
Authors: Li Hui , Deng Baoli , Liu Chunlei , Zou Jian , Ren Huilong 
Published: December 2020

Abstract
A novel matching method has been developed to solve the wave-induced motions and loads of ships with forward speed. The fluid domain is divided into two subdomains by a cylindrical control surface: an interior domain and an exterior domain. Unlike the conventional domain decomposition strategy, the control surface is meshless in present method, on which the physical quantities are expanded into Fourier-Laguerre series. Based on forward speed Green function, the source distribution method is adopted to solve the exterior domain. The calculations of boundary integral equation about forward speed Green function over the control surface are performed analytically, and the solution of exterior domain provides a Dirichlet-to-Neumann (DN) relation on the control surface. In the interior domain, the boundary value problem is solved by Rankine source method. In order to be consistent with exterior solution, the control surface is kept meshless. The ship hull is discretized into constant panels. The free-surface is discretized into cubic B-splines to represent the high-order derivatives of velocity potential precisely. Then, the DN relation is used to close the equation system established in the interior domain. Comparisons with known experimental measurements show that the calculations achieve good accuracy. Furthermore, the influences of numerical method used in the exterior domain are described.
Hydrodynamic Optimization of a Containership
Authors: Feng Yanxin , el Moctar Ould , Schellin Thomas E. 
Published: December 2020

Abstract
Using open-source software Dakota, this paper describes the process of generating an optimal parametric hull shape for a generic containership. Selected design variables defined the ship’s hull, and the influence of these variables on calm water resistance was analyzed. Computations of the flow around the hull were obtained from a validated nonlinear potential flow boundary element method. Using the multi-objective optimization algorithm Surrogate Based Global Optimization (SBGO) reduced the computational effort. The hydrodynamic calm water ship resistance defined the objective function. Compared with the original hull, wave resistance of the optimal hull was significantly reduced for the ship at Froude numbers corresponding to its design speeds.
Maneuvering and Seakeeping Performance of a Generic Tug Based on Numerical Simulations
Authors: Zheng Yingying , Jin Yuting , Yiew Lucas J. , Magee Allan R. 
Published: December 2020

Abstract
Autonomous tugs may play an important role in future ports, due to the shortage of qualified mariners. A digital twin (mathematical model incorporating a vessel’s hydrodynamic behavior and response, suitable for real-time control) would be needed for autonomous operations. Yet, partly because tugs are generally high-powered and very maneuverable compared to conventional vessels, there is little published data on the hydrodynamic performance of such vessels. As a first step in the development of the tug’s digital twin, the present work studies the maneuvering and seakeeping performance of a generic tug at model scale. Numerical simulations are performed for an approximately 1:10 scale model for standard resistance, static and dynamic captive and seakeeping cases. Reynolds-Averaged Navier-Stokes (RANS) k-ω model is employed for the simulations including the free surface through the Volume of Fluid approach. The hydrodynamic forces and moments on the tug model in the simulations of the standard resistance and the static and dynamic captive cases, as well as the tug model’s motions and the added resistance in headseas, are investigated. The simulation results provide data to build a mathematical maneuvering model for the tug based on 4-DoF MMG manoeuvring model, which serves as the digital twin in this case.
Characterization of Magnetic Field in Crack Propagation Stage and Application to Non-Destructive Evaluation
Authors: Bao Sheng , Zhao Zhengye , Luo Qiang , Yang Jian 
Published: December 2020

Abstract
Monitoring of fatigue crack propagation is very important in industrial fields. Stress-induced magnetic measurement is a newly developed non-destructive testing technique which can detect early failure of ferromagnetic materials in service. A lot of experiments demonstrate that magnetic measurement is more sensitive compared with other non-destructive testing technologies. In order to explore the correlation between crack propagation and magnetic hysteresis under cyclic stress in X70 pipeline steel, a series of stress-controlled tests were carried out and the changes in magnetic field around cracks during their propagation process were observed throughout the tension-tension fatigue tests. The variations of magnetic field and stress intensity factor K in the crack propagation stage were studied. The results obtained allowed the division of the magnetic behavior of the investigated steels into three stages corresponding to three distinct crack propagation stages. It was found that the magnetic field varies with crack propagation, and the stress intensity factor K increased with the increase of loading cycles. A strong correlation between the variation of the magnetic field and stress intensity factor was recognized, regardless of the loading conditions, maximum load or stress ratio. The results suggest that non-destructive evaluation of fatigue cracks would be possible using this relationship.
Evaluation of the Frozen Ground for Developing Construction Technology of Pipelines in Cold Regions
Authors: Kim YoungSeok , Kim Sewon 
Published: December 2020

Abstract
Cold regions, such as Alaska, Russia and Canada, get attention from many countries due to the tremendous amount of natural resources which are buried there. An accurate evaluation of the frozen ground is very important because the behavior of the active layer is greatly affected by the soil characteristics and water content in the active layer. It is necessary for developing a construction technology for pipelines in cold regions. This study has two objectives: 1) First one is to evaluate the characteristics of a newly-produced insulated aggregate and 2) the other one is to check the applicability of insulated aggregate. A series of laboratory experiments (specific gravity test, sieve analysis test, direct shear test, test for abrasion of coarse and aggregates by use of the Los Angeles machine) were performed to estimate the characteristics of the newly-produced insulated aggregate. In addition, the laboratory chamber tests were carried out to evaluate the applicability of frozen soil behavior using the newly-produced insulated aggregate. The chamber tests were conducted to check the laboratory model surrounded by soil mixing the insulated aggregate and ordinary soil in order to prevent the damage of structures such as pipelines due to the ground being frozen. For the laboratory chamber tests, the extreme cold engineering laboratory was built within the Yeon Cheon SOC Demonstration Research Center, of the Korea Institute of Construction Technology. The performance of the frozen ground which was installed with the insulated aggregate using vinyl was evaluated through monitoring the time-dependent distribution of temperature and earth-pressure.
Free Fall Water Entry of a Two-Dimensional Asymmetric Wedge in Oblique Slamming: A Numerical Study
Authors: Hosseinzadeh Saeed , Izadi Mohammad , Tabri Kristjan 
Published: December 2020

Abstract
This paper examines the hydrodynamic problem of a two-dimensional symmetric and asymmetric wedge water entry through freefall motion. The gravity effect on the flow is considered and because of precise simulation close to the real phenomenon, the oblique slamming is analyzed. The defined problem is numerically studied using SIMPLE and HRIC schemes and by implementing an overset mesh approach. In order to evaluate the accuracy of the numerical model, the present results are compared and validated with previous experimental studies and showed good agreement. The results are presented and compared for each symmetry and asymmetry in different deadrise angles, drop heights and heel angles. Based on a comparison of the measured vertical acceleration of the experimental wedge data, it is determined that the proposed numerical method has relatively good accuracy in predicting the slamming phenomenon and wedge response. The influence of viscous regime on water entry simulations is investigated, in according to results, effect of viscosity is negligible. Results show that the heel angle dramatically affects the wedge dynamics, pile-up evolution, and pressure distribution. These results suggest evidence for a complex interaction between geometric parameters on the water entry of rigid wedges, which could finally develop our understanding of planing vessels operating in real sea conditions.
Validation of the Master Curve Approach With Various Welding Conditions: Groove Shapes, Heat Inputs and Welding Processes
Authors: Lee Jin Ho , Kim Ji Hoon , Kim Myung Hyun 
Published: December 2020

Abstract
Engineering critical assessment (ECA) is a procedure for evaluating the soundness of structures with flaws and has been widely applied for assessing the structural integrity. ECA procedure requires reliable fracture toughness data to assess the effect of defects. Ideal data are typically obtained from samples taken during construction of an engineering structure or from the structure afterward, but there are cases in which removal of the test samples is impossible due to the continued operation of the structure. To this end, Appendix J of the BS 7910 provides a procedure for estimating fracture toughness values from appropriate Charpy impact test data. However, the correlation between Charpy impact energy and fracture toughness is known to be overly conservative with not sufficient theoretical background in fracture mechanics perspective. In this regard, the revised BS 7910:2019 provides an improved method for calculating the reference temperature by applying the yield strength and the Charpy upper shelf energy based on empirical data.
The target of this study is to validate the master curve approach in the modified BS 7910 for two common offshore grade steels with explicit considerations for various groove shapes, heat inputs and welding processes. For the purpose, the master curves are compared in terms of the reference temperature calculated from Charpy impact test according to BS 7910:2013 and the newly revised 2019 version of BS 7910. The modified master curve resulted in less conservative fracture toughness values anticipated from the decreased reference temperature. The estimated fracture toughness values exhibited a good correlation with experimentally obtained toughness values. The influence of various groove shapes, heat inputs and welding processes in estimating fracture toughness based on the master curve approach is discussed. In addition, the effect of impact test sample locations within weld metals toward estimated fracture toughness values is evaluated.
Relation Between Atmospheric Circulation Patterns in the North Atlantic and the Sea States in the Iberian Peninsula
Authors: Lucas C. , Bernardino M. , Guedes Soares C. 
Published: December 2020

Abstract
A statistical analysis of significant wave height (Hs) in eight locations offshore Portugal continental coast is performed. Specifically, locations at different water depths at Aguçadoura, Leixões, Nazaré, Peniche, Sines and Faro were chosen. The spectral and parametric information from these points used in this analysis was obtained from 21-year hindcast simulations using the spectral wave model SWAN. The modelling of the climatic variability of directional spectra provides reliable information of the most relevant parameters at these locations, i.e., how the spectral parameters and their probability of occurrence change in the regions studied. The occurrences of spectral classes are estimated, and for each class, the variability of the spectral parameters is described by means of joint distributions. The classification of the different sea states provides important information about the wave conditions present in the target areas. A relation between the sea states and the Lamb weather types (WTs), a methodology for classifying atmospheric circulation patterns, is presented in this study. The results of this study provide a description of the wave climate, through the interaction between the sea states and weather patterns, relating different circulation patterns to different sea states. This study provides useful information on the wave conditions that can be used in the design of ocean engineering structures, in the assessment of the operability and safety of shipping and renewable energy devices.
Deep Sea Mining: Towards Conceptual Design for Underwater Transportation
Authors: Vamråk Solheim Astrid , Lesage Maxime , Asbjørnslett Bjørn Egil , Erikstad Stein Ove 
Published: December 2020

Abstract
This paper presents the first steps towards conceptual design for the underwater transportation of minerals from seabed to shore for deep sea mining (DSM). The methodology is based on conceptual design using a systematic approach. Abstraction was used to identify the fundamental entities of the problem, and a function structure containing the overall function and subfunctions was established based on the abstraction. Further, an extensive search for working principles (WP) was conducted in order to find forms associated with the functions. This was done by exploration of solutions within different industries such as the oil and gas industry, subsea industry and dredging industry. The discovered working principles were then listed and categorized based on their physical principles, i.e. classifying criteria. For each function, the working principles were combined into design catalogues with classifying criteria in the rows and columns. Further, compatibility between principles was reviewed. This led to the selection of four working structure sets: one based on ore moved as bulk, and three based on ore moved inside a container. The container-based solutions are different in how the container is moved: inside the cargo hold, carried outside, or towed by underwater vehicle. A completion of the last steps of the conceptual design process is needed to obtain a principle solution.
A Three-Dimensional FE Approach for the Fatigue Analysis of Flexible Pipes Tensile Armors Inside End Fittings
Authors: Miyazaki Marcelo N. R. , de Sousa José Renato M. , Ellwanger Gilberto B. , da Silva Vinicius R. 
Published: December 2020

Abstract
During the end fitting (EF) assembly, the tensile armors of flexible pipes are folded and then unfolded to allow the assessment to the inner sheath and the activation of the inner sealing system. This procedure leaves residual stresses and plastic deformations on these armors, which affect their fatigue resistance and, consequently, the overall performance of the pipe. Hence, in this work, a methodology to predict the fatigue resistance of tensile armors inside an EF is proposed. This methodology relies on stresses calculated with a previously presented three-dimensional finite element (FE) approach and is employed to analyze the fatigue response of a 6” production riser in catenary configuration. This fatigue analysis not only addresses the effects from several irregular sea states but also the local stress concentrations associated with the EF assembly and pre-operational tests (e. g., Factory Acceptance Test, FAT). The results obtained indicate that the EF entrance may be a critical point for fatigue failure and, moreover, the lower fatigue resistance is related to a region where higher alternate stresses occur despite the very high mean stresses are observed in other regions along the tensile armors.
A Discrete Element Model for Brash Ice Simulations
Authors: Behnen Jonas , Hisette Quentin , Ehlers Sören , von Bock und Polach Rüdiger U. Franz 
Published: December 2020

Abstract
Most merchant ships operating in the cold regions are not able to break ice themselves, they can only navigate in the broken ice, the so-called brash ice channels. Today’s standard requires a model test in real brash ice conditions to be carried out and realistic additional resistances to be estimated from this. The problem is that they can only be performed at the end of the design process. The possibility of changing the ship design within the development process can only be guaranteed by using a simulation tool, based on the Discrete Element Method. The problem with the development of this numerical simulation is the correctness of the mapping of the physical behaviour of brash ice. The physical models used are often simplified and not sufficient to represent the complex mechanical behaviour of brash ice. Thus, another problem with the use of numerical simulation is the selection of the correct parameters to describe the mechanical behaviour. A concrete definition of the used material parameters does not exist and the experimental tests for the determination of the physical properties are often complex and not standardized. This paper examines the mechanical behaviour of brash ice and the descriptive parameters of each ice rubble. On this basis, the physical behaviour in nature is compared with the model used in numerical simulation. As a result, physical inconsistencies are determined and new solution approaches are proposed, for example in the form of a new contact model, an extension of the friction model or a change of the descriptive particle shape.
Artificial Intelligence Based Approach for Predicting Fatigue Strength Using Composition and Process Parameters
Authors: Keprate Arvind , Ratnayake R. M. Chandima 
Published: December 2020

Abstract
Accurate prediction of the fatigue strength of steels is vital, due to the extremely high cost (and time) of fatigue testing and the often fatal consequences of fatigue failures. The work presented in this paper is an extension of the previous paper submitted to OMAE 2019. The main objective of this manuscript is to utilize Artificial Intelligence (AI) to predict fatigue strength, based on composition and process parameters, using the fatigue dataset for carbon and low alloy steel available from the National Institute of Material Science (NIMS) database, MatNavi. A deep learning framework Keras is used to build a Neural Network (NN), which is trained and tested on the data set obtained from MatNavi. The fatigue strength values estimated using NN are compared to the values predicted by the gradient boosting algorithm, which was the most accurate model in the OMAE 2019 paper. The comparison is done using metrics such as root mean square error (RMSE), Mean Absolute Error (MAE), Coefficient of Determination (R2) and Explained Variance Score (EVS). Thereafter, the trained NN model is used to make predictions of fatigue strength for the simulated data (1 million samples) of input parameters, which is then used to generate conditional probability tables for the Bayesian Network (BN). The main advantage of using BN over previously used machine learning algorithms is that BN can be used to make both forward and backward propagation during the Bayesian inference. A case study illustrating the applicability of the proposed approach is also presented. Furthermore, a dashboard is developed using PowerBI, which can be used by practicing engineers to estimate fatigue strength based on composition and process parameters.
Dynamic Ship Domain Model Based on AIS Data for Inland Waterways
Authors: He Yankang , Zhang Di , Zhang Jinfen , Wu Bing , Guedes Soares Carlos 
Published: December 2020

Abstract
The existing ship domain models are mostly based on the navigation behavior of open water vessels, and they are not practicable to directly apply to inland rivers. Therefore, it is necessary to establish an inland ship safety domain model based on the ship traffic characteristic therein. Based on the AIS data in the Yangtze River, this paper establishes the functional relationship between these data through multiple regression analysis using data such as ship spacing, ship length, ship speed, and heading angle. Based on this, the safety distance between ships of different lengths in different situations and other ships is determined, so as to establish a dynamic ship domain model. At the same time, this paper explores the geographical relationship between ship and channel boundary and incorporates it into the ship domain model. Finally, a quantitative approach for ship collision risk is proposed, and the collision threat degree is calculated according to the relative heading of the ship and the position in the dynamic ship domain model. Two case studies, including crossing and overtaking situations, are performed to validate the proposed model.
Machine Learning Approach for Estimating Residual Stresses in Girth Welds of Topside Piping
Authors: Bhardwaj Sachin , Ratnayake R. M. Chandima , Keprate Arvind , Ficquet Xavier 
Published: December 2020

Abstract
Residual stresses are internal self-equilibrating stresses that remain in the component even after the removal of external load. The aforementioned stress when superimposed by the operating stresses on the offshore piping, enhance the chances of fracture failure of the components. Thus, it is vital to accurately estimate the residual stresses in topside piping while performing their fitness for service (FFS) evaluation. In the present work, residual stress profiles of girth welded topside sections of P91 pipes piping are estimate using a machine learning approach. The training and testing data for machine learning is acquired from experimental measurements database by Veqter, UK. Twelve different machine learning algorithms, namely, multi-linear regression (MLR), Random Forest (RF), Gaussian process regression (GPR), support vector regression (SVR), Gradient boosting (GB) etc. have been trained and tested. In order to compare the accuracy of the algorithms, four metrics, namely, Root Mean Square Error (RMSE), Estimated Variance Score (EVS), Maximum Absolute Error (AAE), and Coefficient of Determination (R^2) are used. Gradient boosting algorithm gives the best prediction of the residual stress, which is then used to estimate the residual stress for the simulated input parameter space. In the future work authors shall utilize the residual stress predictions from Gradient boosting algorithm to train the Bayesian Network, which can then be used for estimating less conservative through-thickness residual stresses distribution over a wide range of pipe geometries (radius to thickness ratio) and welding parameters (based on heat input). Furthermore, besides topside piping, the proposed approach finds its potential applications in structural integrity assessment of offshore structures, and pressure equipment’s girth welds.