Browsing by Author "Nunez, Marco"

Now showing 1 - 2 of 2
  • Thumbnail Image
    ItemOpen Access
    Design exploration for engineering design optimisation : an aircraft conceptual perspective
    (Cranfield University, 2010-11) Nunez, Marco; Guenov, Marin D.
    Most of the efforts in optimisation so far have been focused on the development of novel or the improvement of existing numerical methods for an effective computation of optimal solutions. Particular attention has been put on balancing multiple conflicting objectives, handling the interaction between different disciplines, reducing computational cost and managing uncertainty. Nonetheless, specific issues of this design methodology still remain to be properly addressed. In this research, attention is concentrated on advancing engineering optimisation as a tool for design exploration. The work is put in the context of conceptual aircraft design. The overall aim of the present research is to develop a methodology that allows the designer to effectively conduct an exploration and analysis of alternative design solutions via a set of methods that can be used separately or conjointly. The initial part of the thesis introduces two novel methods for assisting the formulation of an optimisation problem, which generally is assumed to be given a priori. Nonetheless, the correctness of the optimisation statement, which is not addressed by established optimisation methods, turns out to be decisive for the feasible design set determination. The designer is thus provided with an adaptive formulation of functional and designvariable constraints, which allows the exploration of further promising solutions initially not contained in the feasible design set. Meaningless results or the loss of important solutions can therefore be partially avoided. In a second instance, attention is focused on the visualisation needs for design exploration. A suitable visualisation methodology has been developed to make the large multidimensional results of complex design optimisation procedures fully readable and explanatory. This is achieved by integrating advanced visualisation techniques which provide the designer with diverse perspectives of the data under study and allow him/her to conduct a number of analysis tasks on it, without the need to be an expert in numerical optimisation methods. Last, but not least, a methodology to address conceptual design change problems is proposed. The decision-maker is enabled to formally state the new design requirements and priorities introduced by the conceptual change via an adequate problem reformulation. All the data previously collected can thus be re-used and exploited to drive an effective exploration of alternative design solutions through design space regions of interest. The evaluation of the proposed methodologies has been carried out with a number of test cases. Analytical examples have been used for the assessment of effectiveness, whereas codes representative of aircraft sizing procedures have been adopted to evaluate the methodologies functionality. A visualisation user interface prototype has also been developed for demonstration and evaluation purposes.
  • Thumbnail Image
    ItemOpen Access
    Multidisciplinary design optimization framework for the pre design stage
    (Springer Science Business Media, 2010-09-30T00:00:00Z) Guenov, Marin D.; Fantini, Paolo; Balachandran, Libish Kalathil; Maginot, Jeremy; Padulo, Mattia; Nunez, Marco
    Presented is a novel framework for performing flexible computational design studies at preliminary design stage. It incorporates a workflow management device (WMD) and a number of advanced numerical treatments, including multi-objective optimization, sensitivity analysis and uncertainty management with emphasis on design robustness. The WMD enables the designer to build, understand, manipulate and share complex processes and studies. Results obtained after applying the WMD on various test cases, showed a significant reduction of the iterations required for the convergence of the computational system. The tests results also demonstrated the capabilities of the advanced treatments as follows: The novel procedure for global multi-objective optimization has the unique ability to generate well-distributed Pareto points on both local and global Pareto fronts simultaneously. The global sensitivity analysis procedure is able to identify input variables whose range of variation does not have significant effect on the objectives and constraints. It was demonstrated that fixing such variables can greatly reduce the computational time while retaining a satisfactory quality of the resulting Pareto front. The novel derivative-free method for uncertainty propagation, which was proposed for enabling multi-objective robust optimization, delivers a higher accuracy compared to the one based on function linearization, without altering significantly the cost of the single optimization step.