Browsing by Author "Horsthemke, Hagen Wolfgang"

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    An approach to multi-objective life cycle cost optimization of wind turbine tower structures
    (Stellenbosch : Stellenbosch University, 2013-12) Horsthemke, Hagen Wolfgang; Van der Klashorst, Etienne; Stellenbosch University. Faculty of Engineering. Dept. of Civil Engineering.
    ENGLISH ABSTRACT: Support tower structures of Wind Energy Conversion Systems (WECS) are major cost items and by means of integrated design and optimization, the Life-Cycle Cost (LCC) can be reduced substantially. In this thesis, Horizontal Axis Wind Turbine (HAWTs) tower structures are investigated by means of a technique or tool that can bene t in decision making related situations to reduce the LCC of such WECS support towers from inception to disposal. Often, during the conceptual design phase a certain level of uncertainty or fuzziness exists and plays a role. The central focus in this project is on lattice type towers; however an account on tapered, tubular monopole towers is given as well. The problem is identi ed to be of a multi-objective nature, where a variety of criteria or objectives that are identi ed play a role in the possible reduction of the total LCC of the structure. The study also entails the delineation and discussion of the factors and components that a ect the LCC of a steel structure. The decision maker has control over only a few of these factors and components as identi ed, and these can be formulated by means of an objective to be minimized (or maximized in several other cases). Some of the objectives are incommensurable and others are commensurable with each other. In other words, several of these objectives either `compete' or don't `compete' against each other, respectively. The investigation resulted in the development of a multi-objective LCC optimization using the λ-formulation (or min-max formulation) as the objective aggregating approach for the four objectives identi ed (varied during analysis for sensitivity checks). The objectives are user-de ned in terms of membership functions that grade the degree of membership from total acceptance to total rejection by means of boundary values. This formulation is Non-Pareto based and the decision maker obtains the best trade-o or best compromise solution. The detailed discussion around these objectives is included in the literature study. The objectives in the multi-objective study are weight, cost, perimeter and nodal deflections, and a weighting of the objectives is possible but this is excluded from this study. A Genetic Algorithm (GA), coded in MATLAB, is implemented as the optimization tool or technique. The algorithm uses a quadratic penalty function approach and a natively written Finite Element Analysis (FEA) tool is used for the response model in the tness evaluation process, where the performance for stability, capacity and overall deflections of an individual in the population is quanti ed. A GA has the advantage that it operates on an entire population of individuals using basic principles such as genetics, crossover, mutation, selection and survival of the ttest from biology and Darwinian principles. GAs are very robust and e ective global search methods that can be applied to most elds of study. GAs have previously been e ectively applied in structural, single objective optimization (structural weight) problems. The GA is adopted and modi ed and veri ed with results on academic problems obtained from literature. Satisfactory performance was observed, although room for improvement is identi ed. A case study on a full scale model is performed, using circular hollow sections and equal leg angle sections. These are commonly used steel profi les for lattice type towers. The results obtained are as expected. The structural mass was used as a measure to compare the results. A heavier structure is obtained using the equal leg angle sections compared to the CHS structure with a di fference of up to 20% in weight. The best compromise solutions are feasible and near optimal, given the conditions of the equally weighted objectives in this study. The membership function defi nition and boundary value determination still remains a key issue when using fuzzy logic to incorporate the preference information of the decision maker.