Advanced Techniques for Design and Manufacturing in Marine Engineering

Modern engineering design processes are driven by the extensive use of numerical simulations; naval architecture and ocean engineering are no exception. Computational power has been improved over the last few decades; therefore, the integration of different tools such as CAD, FEM, CFD, and CAM has enabled complex modeling and manufacturing problems to be solved in a more feasible way. Classical naval design methodology can take advantage of this integration, giving rise to more robust designs in terms of shape, structural and hydrodynamic performances, and the manufacturing process.This Special Issue invites researchers and engineers from both academia and the industry to publish the latest progress in design and manufacturing techniques in marine engineering and to debate the current issues and future perspectives in this research area. Suitable topics for this issue include, but are not limited to, the following:CAD-based approaches for designing the hull and appendages of sailing and engine-powered boats and comparisons with traditional techniques;Finite element method applications to predict the structural performance of the whole boat or of a portion of it, with particular attention to the modeling of the material used;Embedded measurement systems for structural health monitoring;Determination of hydrodynamic efficiency using experimental, numerical, or semi-empiric methods for displacement and planning hulls;Topology optimization techniques to overcome traditional scantling criteria based on international standards;Applications of additive manufacturing to derive innovative shapes for internal reinforcements or sandwich hull structures

A knowledge-based engineering tool for aiding in the conceptual design of composite yachts

Proposed in this thesis is a methodology to enable yacht designers to develop innovative structural concepts, even when the loads experienced by the yacht are highly uncertain, and has been implemented in sufficient detail to confirm the feasibility of this new approach. The new approach is required because today's yachts are generally lighter, getting larger and going faster. The question arises as to how far the design envelope can be pushed with the highly uncertain loads experienced by the structure? What are the effects of this uncertainty and what trade-offs in the structural design will best meet the overall design objectives? The new approach provides yacht designers with a means of developing innovative structural solutions that accommodate high levels of uncertainty, but still focus on best meeting design objectives constrained by trade-offs in weight, safety and cost. The designer's preferences have a large, and not always intuitive, influence on the necessary design trade-offs. This in turn invites research into ways to formally integrate decision algorithms into knowledge-based design systems. A lean and robust design system has been achieved by developing a set of tools which are blanketed by a fuzzy decision algorithm. The underlying tool set includes costing, material optimisation and safety analysis. Central to this is the innovative way in which the system allows non-discrete variables to be utilized along with new subjective measures of structural reliability based on load path algorithms and topological (shape) optimisation. The originality in this work is the development of a knowledge-based framework and methodology that uses a fuzzy decision making tool to navigate through a design space and address trade-offs between high level objectives when faced with limited design detail and uncertainty. In so doing, this work introduces the use of topological optimisation and load path theory to the structural design of yachts as a means of overcoming the historical focus of knowledge-based systems and to ensure that innovative solutions can still evolve. A sensitivity analysis is also presented which can quantify a design's robustness in a system that focuses on a global approach to the measurement of objectives such as cost, weight and safety. Results from the application of this system show new and innovative structural solutions evolving that take into account the designers preferences regarding cost, weight and safety while accommodating uncertain parameters such as the loading experienced by the hull

Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

Reducing the Computational Effort Associated with Evolutionary Optimisation in Single Component Design

The dissertation presents innovative Evolutionary Search (ES) methods for the reduction in computational expense associated with the optimisation of highly dimensional design spaces. The objective is to develop a semi-automated system which successfully negotiates complex search spaces. Such a system would be highly desirable to a human designer by providing optimised design solutions in realistic time. The design domain represents a real-world industrial problem concerning the optimal material distribution on the underside of a flat roof tile with varying load and support conditions. The designs utilise a large number of design variables (circa 400). Due to the high computational expense associated with analysis such as finite element for detailed evaluation, in order to produce "good" design solutions within an acceptable period of time, the number of calls to the evaluation model must be kept to a minimum. The objective therefore is to minimise the number of calls required to the analysis tool whilst also achieving an optimal design solution. To minimise the number of model evaluations for detailed shape optimisation several evolutionary algorithms are investigated. The better performing algorithms are combined with multi-level search techniques which have been developed to further reduce the number of evaluations and improve quality of design solutions. Multi-level techniques utilise a number of levels of design representation. The solutions of the coarse representations are injected into the more detailed designs for fine grained refinement. The techniques developed include Dynamic Shape Refinement (DSR), Modified Injection Island Genetic Algorithm (MiiGA) and Dynamic Injection Island Genetic Algorithm (DiiGA). The multi-level techniques are able to handle large numbers of design variables (i.e. > 100). Based on the performance characteristics of the individual algorithms and multi-level search techniques, distributed search techniques are proposed. These techniques utilise different evolutionary strategies in a multi-level environment and were developed as a way of further reducing computational expense and improve design solutions. The results indicate a considerable potential for a significant reduction in the number of evaluation calls during evolutionary search. In general this allows a more efficient integration with computationally intensive analytical techniques during detailed design and contribute significantly to those preliminary stages of the design process where a greater degree of analysis is required to validate results from more simplistic preliminary design models

Composite Materials in Design Processes

The use of composite materials in the design process allows one to tailer a component’s mechanical properties, thus reducing its overall weight. On the one hand, the possible combinations of matrices, reinforcements, and technologies provides more options to the designer. On the other hand, it increases the fields that need to be investigated in order to obtain all the information requested for a safe design. This Applied Sciences Special Issue, “Composite Materials in Design Processes”, collects recent advances in the design methods for components made of composites and composite material properties at a laminate level or using a multi-scale approach

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments

An interactive design environment for coal piping system

The design of coal piping system of a coal-fired power plant is a complex and time-consuming engineering task that involves meeting of several design objectives and constraints. The distribution of coal particles in a pneumatic pipeline can be highly inhomogeneous. Current coal piping design technology relies on empirical model and does not consider particle distribution characteristics in the pipe. In this thesis, a design tool which couples a validated detailed pipe model and an interactive optimization algorithm is developed. This new design tool uses evolutionary algorithms (EAs) as the optimization algorithm, and computational fluid dynamics (CFD) as the evaluation mechanism. The process uses an iterative approach that allows design to be evaluated using CFD analysis automatically to optimize several criteria. The proposed design change is then re-meshed and displayed. Three fundamentally different techniques from traditional optimization methods were considered in order to reduce computation time. Firstly, the tool has been implemented in a virtual engineering environment using VE-Suite. Secondly, the system is integrated with a general interface to allow users to set up the design procedure and interact or guide the searching path as the design evolves. Thirdly, a fast calculation approach is used to reduce the time for single CFD case. The proposed interactive design tool is analyzed and enhanced so that it is usable by the general engineering community. A real coal pipe application was carried out using this design tool. The main objective is to distribute coal flow to its two branches as uniform as possible. The results of this work suggested that the optimum coal pipe can be found relatively fast even when using high-fidelity CFD solver as the analysis method, and the optimum pipe can greatly reduce the coal flow unbalance. This indicates that the tool presented in this thesis can be used as a new and efficient design environment for coal pipe