Set-based approach to passenger aircraft family design

Presented is a method for the design of passenger aircraft families. Existing point-based methods found in the literature employ sequential approaches in which a single design solution is selected early and is then iteratively modified until all requirements are satisfied. The challenge with such approaches is that the design is driven toward a solution that, although promising to the optimizer, may be infeasible due to factors not considered by the models. The proposed method generates multiple solutions at the outset. Then, the infeasible solutions are discarded gradually through constraint satisfaction and set intersection. The method has been evaluated through a notional example of a three-member aircraft family design. The conclusion is that point-based design is still seen as preferable for incremental (conventional) designs based on a wealth of validated empirical methods, whereas the proposed approach, although resource-intensive, is seen as more suited to innovative designs

Design exploration for engineering design optimisation : an aircraft conceptual perspective

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.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Computational design process modeling

In the conceptual design phase, relatively simple equations and functions (or compiled code) are used to describe the aircraft and to perform trade-off studies. The latter require an optimal execution sequence in order to reduce computational cost and design time, respectively. The focus of this paper is the dynamic derivation of the optimal computational plan for each study so that the designer could focus on designing the aircraft rather than managing the process flow. Two methodologies, the Design Structure Matrix (DSM) and the Incidence Matrix are used for the computational process modeling. The incidence matrix describes the relationship between variables and equations/models. The DSM has been used to express the dependency relationships between the models and also, after manipulation, to produce the solution process. The designer specifies the independent (known) variables first. Then the variable flow is modeled using the Incidence Matrix Method (IMM). It determines how data flows through the models, and also identifies any strongly connected components (SCCs). The second step is to rearrange all equations/models hierarchically in order to reduce the feedback loops in each of the identified SCCs. This is achieved by the application of a genetic-based algorithm. Subsequently all SCCs and noncoupled models are assembled into a macro model which forms a global DSM. The global DSM is further rearranged to obtain an upper triangular matrix which defines the final model execution sequence. A simple aircraft sizing example is presented to illustrate the proposed method and algorithm. Advantages of the method include improved efficiency and the ability to deal with both algebraic and numerical models as well as with multiple outputs per model

Computational workflow management for conceptual design of complex systems : an air-vehicle design perspective

The decisions taken during the aircraft conceptual design stage are of paramount importance since these commit up to eighty percent of the product life cycle costs. Thus in order to obtain a sound baseline which can then be passed on to the subsequent design phases, various studies ought to be carried out during this stage. These include trade-off analysis and multidisciplinary optimisation performed on computational processes assembled from hundreds of relatively simple mathematical models describing the underlying physics and other relevant characteristics of the aircraft. However, the growing complexity of aircraft design in recent years has prompted engineers to substitute the conventional algebraic equations with compiled software programs (referred to as models in this thesis) which still retain the mathematical models, but allow for a controlled expansion and manipulation of the computational system. This tendency has posed the research question of how to dynamically assemble and solve a system of non-linear models. In this context, the objective of the present research has been to develop methods which significantly increase the flexibility and efficiency with which the designer is able to operate on large scale computational multidisciplinary systems at the conceptual design stage. In order to achieve this objective a novel computational process modelling method has been developed for generating computational plans for a system of non-linear models. The computational process modelling was subdivided into variable flow modelling, decomposition and sequencing. A novel method named Incidence Matrix Method (IMM) was developed for variable flow modelling, which is the process of identifying the data flow between the models based on a given set of input variables. This method has the advantage of rapidly producing feasible variable flow models, for a system of models with multiple outputs. In addition, criteria were derived for choosing the optimal variable flow model which would lead to faster convergence of the system. Cont/d.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Efficient method for variance-based sensitivity analysis

Presented is an efficient method for variance-based sensitivity analysis. It provides a general approach to transforming a sensitivity problem into one uncertainty propagation process, so that various existing approximation techniques (for uncertainty propagation) can be applied to speed up the computation. In this paper, formulations are deduced to implement the proposed approach with one specific technique named Univariate Reduced Quadrature (URQ). This implementation was evaluated with a number of numerical test-cases. Comparison with the traditional (benchmark) Monte Carlo approach demonstrated the accuracy and efficiency of the proposed method, which performs particularly well on the linear models, and reasonably well on most non-linear models. The current limitations with regard to non-linearity are mainly due to the limitations of the URQ method used

Neutral description and exchange of design computational workflows

Proposed in this paper is a neutral representation of design computational workflows which allows their exchange and sharing between different project partners and across design stages. This is achieved by the de-coupling of configuration and execution logic. Thus, the same underlying workflow can be executed with different (fidelity) models and different software tools as long as the inputs and outputs of the constituent process are kept the same. To this purpose, an object model is proposed to define different simulation objects, their scope, and hierarchy in the simulation process. An XML based computer readable representation of workflows based on the proposed object model, is also suggested. The application of the proposed representation is demonstrated via a case study involving the exchange of workflows between two design partners. The case study also demonstrates how the same workflow can be executed using different execution tools and involving different fidelity models

Interactive uncertainty allocation and trade-off at early-stage aircraft computational design

A common probabilistic approach to uncertainty allocation is to assign acceptable variability in the sources of uncertainty, such that pre-specified probabilities of meeting performance constraints are satisfied. However, the computational cost of obtaining the associated trade-offs increases significantly when more sources of uncertainty and more outputs are considered. Consequently, visualizing and exploring the trade-off space becomes increasingly difficult, which, in turn, makes the decision-making process cumbersome for practicing designers. To tackle this problem, proposed is a parameterization of the input probability distribution functions, to account for several statistical moments. This, combined with efficient uncertainty propagation and inverse computation techniques, results in a computational system which performs order(s) of magnitude faster, compared with a combination of Monte Carlo Simulation and optimization techniques. Also, to aid decision-making regarding the potential combinations of uncertainty allocation, enablers for visualizing the trade space are proposed. The combined approach is demonstrated by means of a representative aircraft thermal system integration example

Aircraft systems architecting: a functional-logical domain perspective

Presented is a novel framework for early systems architecture design. The framework defines data structures and algorithms that enable the systems architect to operate interactively and simultaneously in both the functional and logical domains. A prototype software tool, called AirCADia Architect, was implemented, which allowed the framework to be evaluated by practicing aircraft systems architects. The evaluation confirmed that, on the whole, the approach enables the architects to effectively express their creative ideas when synthesizing new architectures while still retaining control over the process

Interactive uncertainty allocation and trade-off for early-stage design of complex systems

A common probabilistic approach to perform uncertainty allocation is to assign acceptable variability in the sources of uncertainty, such that prespecified probabilities of meeting performance constraints are satisfied. However, the computational cost of obtaining the associated tradeoffs increases significantly when more sources of uncertainty and more outputs are considered. Consequently, visualizing and exploring the decision (trade) space becomes increasingly difficult, which, in turn, makes the decision-making process cumbersome for practicing designers. To address this problem, proposed is a parameterization of the input probability distribution functions, to account for several statistical moments. This, combined with efficient uncertainty propagation and inverse computation techniques, results in a computational system that performs order(s) of magnitude faster than a state-of-the-art optimization technique. The approach is demonstrated by means of an illustrative example and a representative aircraft thermal system integration example

Evolvability and design reuse in civil jet transport aircraft

A comprehensive investigation of evolvability and design reuse in new and historical civil jet transport aircraft was undertaken. The main purpose was to characterise the techniques and strategies used by aircraft manufacturers to evolve their designs. Such knowledge is essential to devise improved design methods for promoting the evolvability of new aircraft. To perform the study, jet aircraft from three large western manufacturers (Boeing, Airbus, and McDonnell Douglas) were investigated in depth. The academic and industrial literature was combed to find descriptions of design reuse and change across each major model of all three manufacturers. The causes and effects of the changes are explored, and the amenability of the different airframes to change are discussed. The evolution of the payload and range capabilities of the different aircraft was also investigated. From these studies, it was found that the initial approach to derivative designs appears somewhat ad hoc and that substantial modifications were devised in quick succession to increase both range and capacity. From the 1970s, two distinguishable patterns started to appear – a ‘leap and branch’ and a ‘Z’ pattern. The leaps correspond to major changes in both propulsion and airframe, whereas the branches are simple ‘stretches’ or ‘shrinks’. The Z pattern, also documented by other authors, is a progressive increase in range, followed by a simple stretch, and then another increase in range. Design changes were investigated further by grouping them according to the assumed payload-range objectives set for the derivatives. Finally, the maximum changes found for salient geometrical design parameters amongst all the aircraft surveyed were documented. Developing methods to support the creation of leaps (especially across configurations) appears to be one of the most promising avenues for future research