The application of multi-objective robust design methods in ship design

When designing large complex vessels, the evaluation of a particular design can be both complicated and time consuming. Designers often resort to the use of concept design models enabling both a reduction in complexity and time for evaluation. Various optimisation methods are then typically used to explore the design space facilitating the selection of optimum or near optimum designs. It is now possible to incorporate considerations of seakeeping, stability and costs at the earliest stage in the ship design process. However, to ensure that reliable results are obtained, the models used are generally complex and computationally expensive. Methods have been developed which avoid the necessity to carry out an exhaustive search of the complete design space. One such method is described which is concerned with the application of the theory of Design Of Experiments (DOE) enabling the design space to be efficiently explored. The objective of the DOE stage is to produce response surfaces which can then be used by an optimisation module to search the design space. It is assumed that the concept exploration tool whilst being a simplification of the design problem, is still sufficiently complicated to enable reliable evaluations of a particular design concept. The response surface is used as a representation of the concept exploration tool, and by it's nature can be used to rapidly evaluate a design concept hence reducing concept exploration time. While the methodology has a wide applicability in ship design and production, it is illustrated by its application to the design of a catamaran with respect to seakeeping. The paper presents results exploring the design space for the catamaran. A concept is selected which is robust with respect to the Relative Bow Motion (RBM), the heave, pitch and roll at any particular waveheading. The design space is defined by six controllable design parameters; hull length, breadth to draught ratio, distance between demihull centres, coefficient of waterplane, longitudinal centre of floatation, longitudinal centre of buoyancy, and by one noise parameter, the waveheading. A Pareto-optimal set of solutions is obtained using RBM, heave, pitch and roll as criteria. The designer can then select from this set the design which most closely satisfies their requirements. Typical solutions are shown to yield average reductions of over 25% in the objective functions when compared to earlier results obtained using conventional optimisation methods

Design Issues for Generalized Linear Models: A Review

Generalized linear models (GLMs) have been used quite effectively in the modeling of a mean response under nonstandard conditions, where discrete as well as continuous data distributions can be accommodated. The choice of design for a GLM is a very important task in the development and building of an adequate model. However, one major problem that handicaps the construction of a GLM design is its dependence on the unknown parameters of the fitted model. Several approaches have been proposed in the past 25 years to solve this problem. These approaches, however, have provided only partial solutions that apply in only some special cases, and the problem, in general, remains largely unresolved. The purpose of this article is to focus attention on the aforementioned dependence problem. We provide a survey of various existing techniques dealing with the dependence problem. This survey includes discussions concerning locally optimal designs, sequential designs, Bayesian designs and the quantile dispersion graph approach for comparing designs for GLMs.Comment: Published at http://dx.doi.org/10.1214/088342306000000105 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Estimator Selection: End-Performance Metric Aspects

Recently, a framework for application-oriented optimal experiment design has been introduced. In this context, the distance of the estimated system from the true one is measured in terms of a particular end-performance metric. This treatment leads to superior unknown system estimates to classical experiment designs based on usual pointwise functional distances of the estimated system from the true one. The separation of the system estimator from the experiment design is done within this new framework by choosing and fixing the estimation method to either a maximum likelihood (ML) approach or a Bayesian estimator such as the minimum mean square error (MMSE). Since the MMSE estimator delivers a system estimate with lower mean square error (MSE) than the ML estimator for finite-length experiments, it is usually considered the best choice in practice in signal processing and control applications. Within the application-oriented framework a related meaningful question is: Are there end-performance metrics for which the ML estimator outperforms the MMSE when the experiment is finite-length? In this paper, we affirmatively answer this question based on a simple linear Gaussian regression example.Comment: arXiv admin note: substantial text overlap with arXiv:1303.428

A robust design methodology suitable for application to one-off products

Robust design is an activity of fundamental importance when designing large, complex, one-off engineering products. Work is described which is concerned with the application of the theory of design of experiments and stochastic optimization methods to explore and optimize at the concept design stage. The discussion begins with a description of state-of-the-art stochastic techniques and their application to robust design. The content then focuses on a generic methodology which is capable of manipulating design algorithms that can be used to describe a design concept. An example is presented, demonstrating the use of the system for the robust design of a catamaran with respect to seakeeping

On Optimal Input Design for Feed-forward Control

This paper considers optimal input design when the intended use of the identified model is to construct a feed-forward controller based on measurable disturbances. The objective is to find a minimum power excitation signal to be used in system identification experiment, such that the corresponding model-based feed-forward controller guarantees, with a given probability, that the variance of the output signal is within given specifications. To start with, some low order model problems are analytically solved and fundamental properties of the optimal input signal solution are presented. The optimal input signal contains feed-forward control and depends of the noise model and transfer function of the system in a specific way. Next, we show how to apply the partial correlation approach to closed loop optimal experiment design to the general feed-forward problem. A framework for optimal input signal design for feed-forward control is presented and numerically evaluated on a temperature control problem

ME Design and Freeform Fabrication of Compliant Cellular Materials with Graded Stiffness

Typically, cellular materials are designed for structural applications to provide stiffness or absorb impact via permanent plastic deformation. Alternatively, it is possible to design compliant cellular materials that absorb energy via recoverable elastic deformation, allowing the material to spring back to its original configuration after the load is released. Potential applications include automotive panels or prosthetic applications that require repeated, low-speed impact absorption without permanent deformation. The key is to arrange solid base material in cellular topologies that permit high levels of elastic deformation. To prevent plastic deformation, the topologies are designed for contact between cell walls at predetermined load levels, resulting in customized, graded stiffness profiles. Design techniques are established for synthesizing cellular topologies with customized compliance for static or quasi-static applications. The design techniques account for cell wall contact, large scale deformations, and material nonlinearities. Resulting cellular material designs are fabricated with selective laser sintering, and their properties are experimentally evaluated.Mechanical Engineerin

Methodology for designing accelerated aging tests for predicting life of photovoltaic arrays

A methodology for designing aging tests in which life prediction was paramount was developed. The methodology builds upon experience with regard to aging behavior in those material classes which are expected to be utilized as encapsulant elements, viz., glasses and polymers, and upon experience with the design of aging tests. The experiences were reviewed, and results are discussed in detail