Searching for improvement

Engineering design can be thought of as a search for the best solutions to engineering problems. To perform an effective search, one must distinguish between competing designs and establish a measure of design quality, or fitness. To compare different designs, their features must be adequately described in a well-defined framework, which can mean separating the creative and analytical parts of the design process. By this we mean that a distinction is drawn between coming up with novel design concepts, or architectures, and the process of detailing or refining existing design architecture. In the case of a given design architecture, one can consider the set of all possible designs that could be created by varying its features. If it were possible to measure the fitness of all designs in this set, then one could identify a fitness landscape and search for the best possible solution for this design architecture. In this Chapter, the significance of the interactions between design features in defining the metaphorical fitness landscape is described. This highlights that the efficiency of a search algorithm is inextricably linked to the problem structure (and hence the landscape). Two approaches, namely, Genetic Algorithms (GA) and Robust Engineering Design (RED) are considered in some detail with reference to a case study on improving the design of cardiovascular stents

[Report of] Specialist Committee V.4: ocean, wind and wave energy utilization

The committee's mandate was :Concern for structural design of ocean energy utilization devices, such as offshore wind turbines, support structures and fixed or floating wave and tidal energy converters. Attention shall be given to the interaction between the load and the structural response and shall include due consideration of the stochastic nature of the waves, current and wind

Non-linear Robust Identification of a Greenhouse Model using Multi-objective Evolutionary Algorithms

[EN] This paper presents a non-linear climatic model (temperature and humidity), based on first-principles equations, of a greenhouse where roses are to be grown using hydroponic methods. Fitting of model parameters (15 in all) is based on measured data collected during summer in the Mediterranean area. A multi-objective optimisation procedure for estimating a set of non-linear models Theta(P) (Pareto optimal), considering simultaneously several optimisation criteria, is presented. A new multi-objective evolutionary algorithm, (sic)-MOGA, has been designed to converge towards ((Theta) over cap (P)* a reduced but well distributed representation of Theta(P) since good convergence and distribution of the Pareto front J(Theta(P)) is achieved by the algorithm. The set can (Theta) over cap (P)* be used as the basis to choose an optimal model that offers a good trade-off among different optimality criteria that have been established. The procedure proposed is applied to the identification and validation of the greenhouse model presented in the paper. (C) 2007 IAgrE. Published by Elsevier Ltd. All rights reserved.Partially supported by MEC (Spanish government) and FEDER funds: projects DPI2005-07835 and DPI2004-8383-C03-02, and Generalitat Valenciana GV06/026. We would like to thank the R&D+i Linguistic Assistance Office at the Universidad Polite´cnica de Valencia for their help in translating this paper.Herrero Durá, JM.; Blasco, X.; Martínez Iranzo, MA.; Ramos Fernández, C.; Sanchís Saez, J. (2007). Non-linear Robust Identification of a Greenhouse Model using Multi-objective Evolutionary Algorithms. Biosystems Engineering. 98(3):335-346. https://doi.org/10.1016/j.biosystemseng.2007.06.004S33534698

A Review of the State-of-the Art in Marine Hydrodynamics

The purpose of the present paper is to summarise the present situation in the field of marine hydrodynamics. Since the William Froude time there has been considerable development in all fields of marine hydrodynamics, both experimental and particularly in theoretical methods and their numerical implementation. The role of computational methods is becoming more important because modern technology requires analysis of increasingly complex phenomena. The hydrodynamics institutes make efforts to expand their activities through integration of experimental and computational approach in order to be able to successfully answer the increased demands of the related industries

A Review of Traffic Signal Control.

The aim of this paper is to provide a starting point for the future research within the SERC sponsored project "Gating and Traffic Control: The Application of State Space Control Theory". It will provide an introduction to State Space Control Theory, State Space applications in transportation in general, an in-depth review of congestion control (specifically traffic signal control in congested situations), a review of theoretical works, a review of existing systems and will conclude with recommendations for the research to be undertaken within this project

Methodological and empirical challenges in modelling residential location choices

The modelling of residential locations is a key element in land use and transport planning. There are significant empirical and methodological challenges inherent in such modelling, however, despite recent advances both in the availability of spatial datasets and in computational and choice modelling techniques. One of the most important of these challenges concerns spatial aggregation. The housing market is characterised by the fact that it offers spatially and functionally heterogeneous products; as a result, if residential alternatives are represented as aggregated spatial units (as in conventional residential location models), the variability of dwelling attributes is lost, which may limit the predictive ability and policy sensitivity of the model. This thesis presents a modelling framework for residential location choice that addresses three key challenges: (i) the development of models at the dwelling-unit level, (ii) the treatment of spatial structure effects in such dwelling-unit level models, and (iii) problems associated with estimation in such modelling frameworks in the absence of disaggregated dwelling unit supply data. The proposed framework is applied to the residential location choice context in London. Another important challenge in the modelling of residential locations is the choice set formation problem. Most models of residential location choices have been developed based on the assumption that households consider all available alternatives when they are making location choices. Due the high search costs associated with the housing market, however, and the limited capacity of households to process information, the validity of this assumption has been an on-going debate among researchers. There have been some attempts in the literature to incorporate the cognitive capacities of households within discrete choice models of residential location: for instance, by modelling households’ choice sets exogenously based on simplifying assumptions regarding their spatial search behaviour (e.g., an anchor-based search strategy) and their characteristics. By undertaking an empirical comparison of alternative models within the context of residential location choice in the Greater London area this thesis investigates the feasibility and practicality of applying deterministic choice set formation approaches to capture the underlying search process of households. The thesis also investigates the uncertainty of choice sets in residential location choice modelling and proposes a simplified probabilistic choice set formation approach to model choice sets and choices simultaneously. The dwelling-level modelling framework proposed in this research is practice-ready and can be used to estimate residential location choice models at the level of dwelling units without requiring independent and disaggregated dwelling supply data. The empirical comparison of alternative exogenous choice set formation approaches provides a guideline for modellers and land use planners to avoid inappropriate choice set formation approaches in practice. Finally, the proposed simplified choice set formation model can be applied to model the behaviour of households in online real estate environments.Open Acces

Estimating the optimum size of a tidal array at a multi-inlet system considering environmental and performance constraints

This paper investigates the optimum tidal energy converter array density at a tidal inlet by applying surrogate-based optimisation. The SBO procedure comprises problem formulation, design of experiments, numerical simulations, surrogate model construction and constrained optimisation. This study presents an example for the Faro-Olhão Inlet in the Ria Formosa (Portugal), a potential site for tidal in-stream energy extraction. A 35 kW Evopod™ floating tidal energy converter from Oceanflow Energy Ltd. has been used for array size calculations considering two design variables: (1) number of array rows, and (2) number of tidal energy converter per row. Arrays up to 13 rows with 6–11 tidal energy converters each are studied to assess their impacts on array performance, inlets discharges and bathymetry changes. The analysis identified the positive/negative feedbacks between the two design variables in real case complex flow fields under variable bathymetry and channel morphology. The non-uniformity of tidal currents along the array region causes the variability of the resource in each row, as well as makes it difficult to predict the resultant array configuration interactions. Four different multi-objective optimisation models are formulated subject to a set of performance and environmental constraints. Results from the optimisation models imply that the largest array size that meets the environmental constraints is made of 5 rows with 6 tidal energy converter each and an overall capacity factor of 11.6% resulting in an energy production of 1.01 GWh year−1. On the other hand, a higher energy production (1.20 GWh year−1) is achieved by an optimum array configuration, made of 3 rows with 10 tidal energy converters per row, which maximises power output satisfying environmental and performance restrictions. This optimal configuration permits a good level of energy extraction while having a reduced effect on the hydrodynamic functioning of the multi-inlet system. These results prove the suitability and the potential wide use of the surrogate-based optimisation method to define array characteristics that enhance power production and at the same time respect the environmental surrounding conditions.info:eu-repo/semantics/publishedVersio

Reliability Analysis of Continuous Structural Systems

This study mainly deals with developing another approximate method for system reliability analysis and its applications to the continuous structures such as an assembly of stiffened cylindrical and rectangular sections used in Tension Leg Platform (TLP). Various methods developed for the structural system reliability analysis are reviewed The developed system reliability method, called herein the "Extended Incremental Load Method", is an extended approach of the conventional incremental load method. It has been developed in order to extend its applicability to the system reliability analysis of a structure under multiple loadings. It directly uses existing component strength formulae in the system analysis and more realistically takes account of the post-ultimate (post-failure) behaviour of a failed component when assessing the system reliability and ultimate strength. This is an important merit of the method over other methods. The method allows for load re-distribution during the development of elasto-plastic moments in large cross-sections under the action of axial and bending forces and in the presence of lateral hydrostatic and hydrodynamic pressure. The effects of shearing actions are ignored. A search is made for the most important failure modes to give the lowest system safety index. In the method the modified safety margin equation, which has been proposed to use existing strength formulae for principle components of a floating offshore structure, is employed in which the strength modelling parameter is treated as a basic random variable in system reliability analysis as well as component reliability analysis and the concept of the first-order second moment method is adopted to obtain the resistance coefficients and the loading coefficients in the safety margin equation. Details about deriving the safety margin equation by the proposed reliability method, calculation of the total load factor, the procedure of identifying the most important failure modes and flow vectors of principle component are described in the Appendices. Applications to discrete structures are demonstrated to show the validity of the proposed method. The method has been applied to the Hutton TLP and two variants, TLP-A and TLP-B, which are modified models of the Hutton TLP and of the design using TLP Rule Case Committee type loading and improved strength models, under the design environmental loading conditions. Components and systems safety indices of the models, Hutton TLP, TLP-A and TLP-B, are illustrated with three dimensional collapse mechanisms figures. Reserve and reserve strength characteristics are derived for the design as built and for more economical and efficient variations of the design. The TLP form is shown to possess high redundancy and systems safety. Sensitivity studies to changes in stochastic parameters of resistance and loading variables have been carried out. For this purpose the strength modelling parameter, yield stress and certain member sizes are selected as resistance variables, and effects of their mean values and/or coefficients of variation on the system, as well as on the component reliability index, have been investigated. The effects of mean bias and coefficient of variation of load effects, namely, static, quasi-static and dynamic component, on the the system as well as on the component reliability index have also been investigated. The results are discussed with regard to effects of various parameters on safety, with illustrating figures, from which the relative importance of random variables can be seen. As an another important resistance variable, the post-ultimate behaviour of failed components has been taken account of in system reliability assessment, which should be the most important resistance variable affecting the system reliability and the effective residual strength of a structure. Some case studies have been carried out with the simplified non-linear model which has a form of piecewise multi-state (more than two states) and is characterised by the post-ultimate slope and the residual strength. The results are illustrated in figures and tables and discussion made about its effects on the system reliability level. (Abstract shortened by ProQuest.)