Computerized three-dimensional design system for rectangular tile coating on hull surface

To better guide the coating process of rectangular tiles on a ship hull, a computerized three-dimensional design method is proposed. Research was done on a tile generating algorithm, tile laying design flow, tiles gap examination algorithm, and tiles slight displacement, as well as cutting and rotating algorithms.A three-dimensional design system was developed using an MDT platform. The application of this system indicates that using the design arrangement to coat tiles on a ship’s hull can result in enhanced coating quality.

Development of Bayesian Network Models for Risk-Based Ship Design

In the past fifteen years, the attention of ship safety treatment as an objective rather than a constraint has started to sweep through the whole maritime industry. The risk-based ship design （RBD） methodology, advocating systematic integration of risk assessment within the conventional design process has started to takeoff. Despite this wide recognition and increasing popularity, important factors that could potentially undermine the quality of the results come from both quantitative and qualitative aspects during the risk assessment process. This paper details a promising solution by developing a formalized methodology for risk assessment through effective storing and processing of historical data combined with data generated through first-principle approaches. This method should help to generate appropriate risk models in the selected platform （Bayesian networks） which can be employed for decision making at design stare.

Research and development of a digital design system for hull structures

Methods used for digital ship design were studied and formed the basis of a proposed frame model suitable for ship construction modeling. Based on 3-D modeling software, a digital design system for hull structures was developed. Basic software systems for modeling, modifying, and assembly simulation were developed. The system has good compatibility, and models created by it can be saved in different 3-D file formats, and 2D engineering drawings can be output directly. The model can be modified dynamically, overcoming the necessity of repeated modifications during hull structural design. Through operations such as model construction, intervention inspection, and collision detection, problems can be identified and modified during the hull structural design stage. Technologies for centralized control of the system, database management, and 3-D digital design are integrated into this digital model in the preliminary design stage of shipbuilding.

Evaluation and selection of the ship collaborative design resources based on AHP and genetic and simulated annealing algorithm

The characteristics of the design resources in the ship collaborative design is described and the hierarchical model for the evaluation of the design resources is established. The comprehensive evaluation of the co-designers for the collaborative design resources has been done from different aspects using Analytic Hierarchy Process （AHP） ,and according to the evaluation results,the candidates are determined. Meanwhile,based on the principle of minimum cost,and starting from the relations between the design tasks and the corresponding co-designers,the optimizing selection model of the collaborators is established and one novel genetic combined with simulated annealing algorithm is proposed to realize the optimization. It overcomes the defects of the genetic algorithm which may lead to the premature convergenee and local optimization if used individually. Through the application of this method in the ship collaborative design system,it proves the feasibility and provides a quantitative method for the optimizing selection of the design resources.

Internet of Ships: The Future Ahead

There are many advantages of using Computer Aided Design (CAD) Systems in a shipbuilding environment: ease of design, speed of construction, use and reuse of information, etc. It is expected that in future CAD tools will advance further and allow greater information management and virtual access through smart devices. The authors of this paper talk about a new concept in shipbuilding, the Internet-of-Ships (IoS) which would have a deep impact on the ship design and production, with a huge diversity of present and potential applications.

Study of the ship design process model for collaborative design

The ship design process model is the basis for developing the ship collaborative design system under network environment.According to the characteristics of the ship design, a method for dividing the ship design process into three layers is pat forward, that is project layer, design task layer and design activity layer, then the formalized definitions of the ship design process model, the decomposing principles of the ship design process and the architecture of the ship collaborative design (SDPM) system are presented. This method simplifies the activity network, makes the optimization and adjustment of the design plan convenient and also makes the design process easier to control and change, at last the architecture of the ship collaborative design system is discussed.

Knowledge-based engineering approach for the support of ship structure design

The paper presents a knowledge-based engineering （KBE） approach for ship node components design. In the ship design process, many design tasks need design experiences to support. Howev- er, a ship design process is a complicated process with many simultaneously repetitive and time-con- suming activities. In this research, the method combines KBE with Tribon system＇s built-in devel- opment language tools of Vitesse, captures and applies design knowledge for achieving standard com- ponents intelligent design modeling. A case study and industry implementation illustrate the feasibili- ty of the proposed methodology. The KBE technique can provide not only proper references, sug- gests and supports but also knowledge integrated in the ship structure design. Especially, these rules related to the design can avoid lots of design mistakes. During the ship design stage, getting more precise and better designs will not only reduce the time of rework and wasting resources but also shorten the construction time_ imnrov~ clilnl;hz ~nA nrnf;t

Recent Advances to Change the Standards in Designing Hulls in Waves, a Validation Using an Efficient SWENSE Level-Set Approach

This paper presents recent naval applications of the SWENSE （Spectral Wave Explicit Navier-Stokes Equations） approach implemented for the first time with high order fully unstructured schemes and an efficient level-set method to capture free surface flows around realistic hull geometries. Numerical simulations in waves and/or viscous flows still lead generally to very large CPU times because of grid requirements to ensure a good propagation of incident waves in the meshed part of the fluid domain that makes unreachable any hull design optimization process in an industrial context. Furthermore, even if the SWENSE method clearly shows promising results in an academic context in both regular and irregular waves, the most recent publications still highlight several issues that remain unresolved up to now, e.g. poor scalability, diffusive wake pattern, non-versatile structured mesh approaches and only very few validation test cases are carried out on Wigley or DTMB 5415 hulls. In order to overcome those numerical difficulties and get an in-depth validation of the method on several cases in realistic wave conditions, a two and a half years＇ research project has been achieved involving several steps, starting by a set of dedicated model test experiments later used as reference for the validation of the method. The CFD commercial code ANANASTM used and developed in this research program is presented and validated in detail. The use of high order schemes on unstructured grids in combination with these SWENSE method and level-set approach offer to the maritime industry an innovative and state of the art method to achieve unequaled accuracy, low computation time and some unique advantages such as, amongst others, the end of the numerical wave propagation problems. The results of the validation were pleasing and can be considered as acceptable in general, with some challenges remaining to the solyed. Results obtained indicate that an optimization processes in waves in realistic conditions is now affordable in an industrial context.

Research on the Definition and Influence of New Production of Ship Industry Index of Energy Efficiency on the Ship Design Process

In this paper, we conduct research on the definition and influence of new production of ship industry index of energy efficiency on the ship design process. Ship energy saving is the key to energy saving ship form optimization design. In the ship under the conditions of use, and to optimize the design of the hull lines with boat, minimize the ship resistance, with the final choice of ship host fuel-sipping. Our research combine the characteristics of the energy efficiency with the shipbuilding industry with the novel and innovative design pattern which will be meaningful.

Research on the Definition and Influence of New Production of Ship Industry Index of Energy Efficiency on the Ship Design Process

In this paper, we conduct research on the definition and influence of new production of ship industry index of energy efficiency on the ship design process. Ship energy saving is the key to energy saving ship form optimization design. In the ship under the conditions of use, and to optimize the design of the hull lines with boat, minimize the ship resistance, with the final choice of ship host fuel-sipping. Our research combine the characteristics of the energy efficiency with the shipbuilding industry with the novel and innovative design pattern which will be meaningful.

基于水动力载荷混合数据集的高精度神经网络代理模型构建

In this work,we constructed a neural network proxy model(NNPM)to estimate the hydrodynamic resistance in the ship hull structure design process,which is based on the hydrodynamic load data obtained from both the potential flow method(PFM)and the viscous flow method(VFM).Here the PFM dataset is applied for the tuning,pre-training,and the VFM dataset is applied for the fine-training.By adopting the PFM and VFM datasets simultaneously,we aim to construct an NNPM to achieve the high-accuracy prediction on hydrodynamic load on ship hull structures exerted from the viscous flow,while ensuring a moderate data-acquiring workload.The high accuracy prediction on hydrodynamic loads and the relatively low dataset establishment cost of the NNPM developed demonstrated the effectiveness and feasibility of hybrid dataset based NNPM achieving a high precision prediction of hydrodynamic loads on ship hull structures.The successful construction of the high precision hydrodynamic prediction NNPM advances the artificial intelligence-assisted design(AIAD)technology for various marine structures.

Role of Naval Architects in Ship Recycling

The paper identifies twelve elements of ship recycling recycling system. The source and items of knowledgebase for ship and highlights their respective roles and duties in a proposed ship recycling have been brought out. A new philosophy focusing clean and safe ship recycling namely design for ship recycling has been introduced based on principles such as ecofriendliness, engineering efficiency, energy conservation and ergonomics. The role of naval architects in ship recycling industry has been described based on the above factors. The paper brings out the role of naval architects in ship recycling the way it has been practiced worldwide and proposed by regulatory bodies. The authors have brought out the new concept of design for ship recycling and various aspects of it. The role of naval architects in the practice of this new design philosophy which is ready to be embraced by the maritime industry has been reiterated.

An artificial intelligence-aided design (AIAD) of ship hull structures

Ship-hull design is a complex process because the any slight local alteration in ship hull structure may significantly change the hydrostatic and hydrodynamic performances of a ship.To find the optimum hull shape under the design requirements,the state-of-art of ship hull design combines computational fluid dynamics computation with geometric modeling.However,this process is very computationally intensive,which is only suitable at the final stage of the design process.To narrow down the design parameter space,in this work,we have developed an AI-based deep learning neural network to realize a real-time prediction of the total resistance of the ship-hull structure in its initial design process.In this work,we have demonstrated how to use the developed DNN model to carry out the initial ship hull design.The validation results showed that the deep learning model could accurately predict the ship hull’s total resistance accurately after being trained,where the average error of all samples in the testing dataset is lower than 4%.Simultaneously,the trained deep learning model can predict the hip’s performances in real-time by inputting geometric modification parameters without tedious preprocessing and calculation processes.The machine learning approach in ship hull design proposed in this work is the first step towards the artificial intelligence-aided design in naval architectures.

Machine Learning-Based Approach to Liner Shipping Schedule Design

This paper studied a tactical liner shipping schedule design issue under sail and port time uncertainties,which is the determination of the planned arrival time at each port call as well as the punctuality rate and number of assigned ship on the route.A number of studies have tried to introduce the operational speed adjustment measure into this tactical schedule design issue,to alleviate the discrepancies between designed schedule and maritime practice.On the one hand,weather conditions can lead to speed loss phenomenon of ships,which may result in the failure of ships’punctual arrivals.On the other hand,improving the ability of speed adjustment can decrease the late-arrival compensation,but increase the fuel consumption cost.Then,we formulated a machine learning-based liner shipping schedule design model aiming at above-mentioned two limitations on speed adjustment measure.And a machine learning-based approach has been designed,where the speed adjustment simulation,the neural network training and the reinforcement learning were included.Numerical experiments were conducted to validate our results and derive managerial insights,and then the applicability of machine learning method in shipping optimization issue has been confirmed.

Space Modeling Method for Ship Pipe Route Design

Ship pipe route design(SPRD)is one of the most complex and timeconsuming processes in ship detail design.Currently,there are many researches on the optimization of ship pipe routes,but there is still a lack of effective and convenient methods to build the pipe routing space.In order to solve this problem,a piping space modeling method for SPRD is proposed.This method is based on stereo lithographic(STL)file which is commonly used in data exchange,and it can convert the initial space model built in 3D-CAD software into the data model required by the pipe routing algorithms.For the application purpose,a piping space modeling utility(PSMU)is developed with Python and OpenGL,promoting the development of practical pipe routing system.Finally,the feasibility and practicability of the proposed method are verified by the experiment on the piping space of an actual ship fuel system.

A one-dimensional polynomial chaos method in CFD–Based uncertainty quantification for ship hydrodynamic performance

A one-dimensional non-intrusive Polynomial Chaos （PC） method is applied in Uncertainty Quantification （UQ） studies for CFD-based ship performances simulations. The uncertainty properties of Expected Value （EV） and Standard Deviation （SD） are evaluated by solving the PC coefficients from a linear system of algebraic equations. The one-dimensional PC with the Legendre polynomials is applied to： （1） stochastic input domain and （2） Cumulative Distribution Function （CDF） image domain, allowing for more flexibility. The PC method is validated with the Monte-Carlo benchmark results in several high-fidelity, CFD-based, ship UQ problems, evaluating the geometrical, operational and environmental uncertainties for the Delft Catamaran 372. Convergence is studied versus PC order P for both EV and SD, showing that high order PC is not necessary for present applications. Comparison is carried out for PC with/without the least square minimization when solving the PC coefficients. The least square minimization, using larger number of CFD samples, is recommended for current test cases. The study shows the potentials of PC method in Robust Design Optimization （RDO） and Reliability-Based Design Optimization （RBDO） of ship hydrodynamic performances.