Browsing by Author "Molina-Cristobal, Arturo"

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    Aircraft systems architecting: a functional-logical domain perspective
    (American Institute of Aeronautics and Astronautics, 2016-06-17) Guenov, Marin D.; Molina-Cristobal, Arturo; Voloshin, V.; Riaz, Atif; van Heerden, Albert S. J.; Sharma, Sanjiv; Cuiller, C.; Giese, Tim
    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.
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    Civil Transport Aircraft Evolvability Data
    (Cranfield University, 2018-10-15 13:44) Van Heerden, Stevan; Guenov, Marin; Molina-Cristobal, Arturo
    This is an appendix to the paper `Evolvability and Design Reuse in Civil Jet Transport Aircraft', by A.S.J. van Heerden, Marin D. Guenov, and Arturo Molina-Cristobal. It contains data that was used to create the plots and figures in Sections 6, 7, and 8 of the paper.
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    Component-driven computational design of complex engineering systems.
    (2018-08) Bile, Yogesh Hanumant; Guenov, Marin D.; Molina-Cristobal, Arturo
    During the conceptual design of complex systems, architects study a number of different options, which comprise the architectural design space. Usually, new system architectures (SAs) are created by modifying existing ones, e.g., by deleting existing and/or adding new elements. Once the concept is synthesised, the architect wishes to swiftly find the effect of the proposed architectural changes at system level. This would involve sizing of the modified sub-systems, and then, obtaining the system level performance. In turn, this involves time-consuming activities, such as re-arrangement (orchestration) of computational tasks and models. Also, depending on the results, the architect may undertake further modifications. When doing this, a means to navigate across the RFLP (Requirements-Functional-Logical-Physical) views of the SA may be required, in order to trace elements affected by these modifications. Generally, several iterations are involved between architecting and sizing during conceptual design, which, if manually performed, result in a tedious and time-consuming process. There are existing methods which address this problem, but these have significant limitations in that they are usually system specific and often involve an excessive amount of time-consuming manual tasks. Within this context, the research aim is to improve the efficiency of the architectural design space exploration (ADSE) process, by automating repetitive computational tasks, thus enabling the designer to swiftly and interactively explore multiple SA options. A novel method, comprised of two parts, has been developed to achieve the aim. In the first part, a graph-theoretic approach is employed to enable architectural element dependency analysis. Here, the relationships between the architectural elements are stored as a graph. Algorithms, such as ‘Depth First Search’ and ‘Transitive Closure’ are then applied to assist the architect in tracing the dependencies between elements that might be affected by a proposed change to other elements of the SA. In the second part, the architecture is assessed to find the system level performance. The inputs needed for rapid assessment include the functional and logical views of the SA, and the requisite steady-state computational models associated with each of the ‘logical’ components. The assessment process itself consists of three steps. In the first step, the sequence of the sub-systems is automatically generated by extracting a sub-systems source-sink ‘Dependency Structure Matrix (DSM)’ from the logical view, followed by the application of an algorithm which determines the systems’ sizing sequence. In the second step, the individual sub-systems and system level workflows are constructed. Here, the computational workflow (a network of computational models) is represented as a bipartite graph. A maximum matching enumeration algorithm is used to find all possible workflows for a given model set, and another algorithm, to choose from these the most computationally efficient one, i.e., the workflow with the lowest number of reversed variables. In the third step, the workflows produced in the second step and subsystems ’sizing sequence obtained in the first step are combined to produce a complete workflow. To demonstrate and evaluate the proposed enablers, the author developed a prototype object-oriented architecting tool. The enablers were individually and collectively verified on representative test-cases. Comparison with the existing methods confirmed the claimed advantages of the proposed approach, namely, reducing the number of manual activities, which results in swifter and interactive ADSE process. Feedback obtained from experts in the aircraft industry during an initial qualitative evaluation session confirmed the usefulness of the proposed method.
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    Computational framework for interactive architecting of complex systems
    (Wiley, 2020-02-17) Guenov, Marin D.; Riaz, Atif; Bile, Yogesh H.; Molina-Cristobal, Arturo; van Heerden, Albert S. J.
    Presented is a novel framework for interactive systems architecture definition at early design stages. It incorporates graph‐theoretic data structures, entity relationships, and algorithms that enable the systems architect to operate interactively and simultaneously in different domains. It explicitly captures the “zigzagging” of the functional reasoning process, including not only allocated, but also the derived functions. A prototype software tool, AirCADia Architect, was implemented, which allowed the framework to be demonstrated to and tried hands‐on by practicing aircraft systems architects. The tool enables architects to effectively express their ideas when interactively synthesizing new architectures, while still retaining control over the process. The proposed approach was especially acknowledged as the way forward for rationale capture.
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    Computational techniques for aircraft evolvability exploration during conceptual design.
    (2018-02) Van Heerden, Albert Stevan Johan; Guenov, Marin D.; Molina-Cristobal, Arturo
    Evolvability is a critical consideration during the design of an aircraft. It refers to the extent to which a baseline design could be reused, or `easily' modified to create descendant designs that would meet future requirements. Since a major fraction of the cost of an aircraft programme is determined by decisions made during conceptual design, it is essential that the design space is explored thoroughly during this stage to find evolvable designs. Existing computational methods to perform such exploration exist, but are limited in two respects. The first of these is that, with existing techniques, derivatives are usually generated by applying pre-specified modifications to a selected baseline, such that each derivative in a study is only linked to a single baseline. The designer must therefore evaluate large numbers of baseline-derivative pairs to adequately capture the evolution options available. The second limitation concerns an absence of appropriate down-selection criteria to narrow down the number of design points when evolvability is considered. The work presented in this thesis addresses these limitations. The aim was to develop computational techniques that would enable aircraft designers to explore the evolvability of their designs more efficiently and effectively during the conceptual design stage. The scope was limited to civil transport aircraft and specifically to airframes. The work is applicable to both single- and twin-aisle aircraft, but the focus was, to a small degree, more on single-aisles. The research resulted in two main contributions: 1) a framework to provide a means to link all derivatives to all the baselines; and 2) a set of techniques to filter out inferior designs systematically. The framework builds on the premise that the degree of `similarity' between two ,designs could be used as an estimate for the redesign e ort (i.e. resource expenditure) required to change one of these into the other. Case studies involving existing aircraft families were conducted to determine which design changes could be considered `reasonable'. Based on this information, a set of techniques to assess airframe similarity was developed, which involves automatically predicting possible commonality across two designs. Several algorithms were devised to achieve this, including one that solves a longest common subsequence problem to find common body segments and a simple optimisation procedure to find common wing elements. Notably, these techniques can be used to compare aircraft with dissimilar configurations. For testing purposes, the framework was applied to several existing and future aircraft. The results showed that the predicted commonality matches published information regarding commonality and design re-use between designs. The framework essentially removes the need to model each future design option based on a specific starting design. The design filtering techniques involve the application of set-based design to facilitate systematic down-selection of potential designs. Specifically, it is demonstrated how established set-based design criteria could be adapted to prune an evolvability design space progressively. To demonstrate the usefulness of the research, it was applied to an example, concerning design candidates for a new single-aisle, environmentally friendly passenger aircraft. The results of this study were presented to a panel of design specialists from Airbus UK. The panel concluded that the proposed similarity assessment provides reasonable initial estimates for redesign e ort and that the overall approach adds value to the evolvability exploration process.
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    Efficient method for variance-based sensitivity analysis
    (Elsevier, 2018-07-05) Chen, Xin; Molina-Cristobal, Arturo; Guenov, Marin D.; Riaz, Atif
    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.
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    Enablers for uncertainty quantification and management in early stage computational design. An aircraft perspective
    (2017-10) Chen, Xin; Guenov, Marin D.; Molina-Cristobal, Arturo
    Presented in this thesis are novel methods for uncertainty quantification and management (UQ&M) in computational engineering design. The research has been motivated by the industrial need for improved UQ&M techniques, particularly in response to the rapid development of the model-based approach and its application to the (early) design of complex products such as aircraft. Existing work has already addressed a number of theoretical and computational challenges, especially regarding uncertainty propagation. In this research, the contributions to knowledge are within the wider UQ&M area. The first contribution is related to requirements for an improved margin management policy, extracted from the FP7 European project, TOICA (Thermal Overall Integrated Conception of Aircraft). Margins are traditional means to mitigate the effect of uncertainty. They are relatively better understood and less intrusive in current design practice, compared with statistical approaches. The challenge tackled in this research has been to integrate uncertainty analysis with deterministic margin allocations, and to provide a method for exploration and trade-off studies. The proposed method incorporates sensitivity analysis, uncertainty propagation, and the set-based design paradigm. The resulting framework enables the designer to conduct systematic and interactive trade-offs between margins, performances and risks. Design case studies have been used to demonstrate the proposed method, which was partially evaluated in the TOICA project. The second contribution addresses the industrial need to properly ‘allocate’ uncertainty during the design process. The problem is to estimate how much uncertainty could be tolerated from different sources, given the acceptable level of uncertainty associated with the system outputs. Accordingly, a method for inverse uncertainty propagation has been developed. It is enabled by a fast forward propagation technique and a workflow reversal capability. This part of the research also forms a contribution to the TOICA project, where the proposed method was applied on several test-cases. Its usefulness was evaluated and confirmed through the project review process. The third contribution relates to the reduction of UQ&M computational cost, which has always been a burden in practice. To address this problem, an efficient sensitivity analysis method is proposed. It is based on the reformulation and approximation of Sobol’s indices with a quadrature technique. The objective is to reduce the number of model evaluations. The usefulness of the proposed method has been demonstrated by means of analytical and practical test-cases. Despite some limitations for several specific highly non-linear cases, the tests confirmed significant improvement in computational efficiency for high dimensional problems, compared with traditional methods. In conclusion, this research has led to novel UQ&M tools and techniques, for improved decision making in computational engineering design. The usefulness of these methods with regard to efficiency and interactivity has been demonstrated through relevant test-cases and qualitative evaluation by (industrial) experts. Finally, it is argued that future work in this field should involve research and development of a comprehensive framework, which is able to accommodate uncertainty, not only with regard to computation, but also from the perspective of (expert) knowledge and assumptions.
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    Enabling interactive safety and performance trade-offs in early airframe systems design
    (AIAA, 2020-01-05) Jimeno, Sergio; Riaz, Atif; Guenov, Marin D.; Molina-Cristobal, Arturo
    Presented is a novel interactive framework for incorporating both safety and performance analyses in early systems architecture design, thus allowing the study of possible trade-offs. Traditionally, a systems architecture is first defined by the architects and then passed to experts, who manually create artefacts such as Fault Tree Analysis (FTA) for safety assessment, or computational workflows, for performance assessment. The downside of this manual approach is that if the architect modifies the systems architecture, most of the process needs to be repeated, which is tedious and time consuming. This limits the exploration of the design space, with the associated risk of missing better architectures. To overcome this limitation, the proposed framework automates parts of the safety and performance analysis in the context of the Requirement, Functional, Logical, and Physical (RFLP) systems engineering paradigm. Safety analysis is carried out by automatic creation of FTA models from the functional and logical flow views. Regarding performance analysis, computational workflows are first automatically created from the logical flow view, and then executed for a set of flight conditions over the range of the mission in order to determine the most demanding condition. Finally, performance characteristics of the subsystems, such as weights, power offtakes, ram drag etc. are evaluated at the most demanding flight condition, which enables the architect to compare architectures at aircraft level. The framework is illustrated with a representative example involving the design of an environmental control system of a civil aircraft, where the safety and performance trade-off is conducted for multiple ECS architectures.
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    Evolvability and design reuse in civil jet transport aircraft
    (Elsevier, 2019-05-10) van Heerden, Albert S. J.; Guenov, Marin D.; Molina-Cristobal, Arturo
    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.
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    Incorporating safety in early (airframe) systems design and assessment
    (AIAA, 2019-01-14) Jimeno, Sergio; Molina-Cristobal, Arturo; Riaz, Atif; Guenov, Marin D.
    Presented is a novel framework for incorporating safety analysis in early systems architecture design.Traditionally, a systems architecture is first defined by the architects and then passed to safety experts, who manually create artefacts such as Function Hazard Analysis (FHA) or Fault Tree Analysis (FTA) for safety assessment. The problem with this manual approach is that if the architect modifies the systems architecture, then the whole safety assessment process needs to be repeated, which is tedious and time consuming. To overcome this limitation, the proposed framework automates the creation of safety models such as FHA and FTA by utilizing the Requirement, Functional, Logical, and Physical (RFLP) systems engineering paradigm. The framework supports three main activities. First, the safety targets are determined by performing a FHA of the architecture and the Requirements view is updated. Second, compliance with the safety requirements is analyzed using dynamic fault trees, automatically generated from the Logical view. Interactive visualization techniques are proposed to interpret the safety results, e.g. highlighting the greatest contributors to the probability of failure. Third, an algorithm is developed that enables the designer to interactively improve the architecture’s safety by introducing more reliable components or increasing redundancy. The concept is illustrated with a representative example, where the environmental control system of a civil aircraft is studied from a safety point of view.
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    Interactive uncertainty allocation and trade-off at early-stage aircraft computational design
    (AIAA, 2018-01-13) Molina-Cristobal, Arturo; Guenov, Marin D.; Riaz, Atif; van Heerden, Albert S. J.
    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.
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    Interactive uncertainty allocation and tradeoff for early-stage design of complex systems
    (AIAA, 2019-11-20) Molina-Cristobal, Arturo; Chen, Xin; Guenov, Marin D.; Riaz, Atif; van Heerden, Albert S. J.
    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.
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    Margin allocation and trade-off in complex systems design and optimization
    (AIAA, 2018-05-01) Guenov, Marin D.; Chen, Xin; Molina-Cristobal, Arturo; Riaz, Atif; van Heerden, Albert S. J.
    Presented is an approach for interactive margin management. Existing methods enable a fixed set of allowable margin combinations to be identified, but these have limitations with regard to supporting interactive exploration of the effects of: 1) margins on other margins, 2) margins on performance and 3) margins on the probabilities of constraint satisfaction. To this purpose, the concept of a margin space is introduced. It is bi-directionally linked to the design space, to enable the designer to understand how assigning margins on certain parameters limits the allowable margins that can be assigned to other parameters. Also, a novel framework has been developed. It incorporates the margin space concept as well as enablers, including interactive visualization techniques, which can aide the designer to explore the margin and design spaces dynamically, as well as the effects of margins on the probability of constraint satisfaction and on performance. The framework was implemented into a prototype software tool, AirCADia, which was used for a qualitative evaluation by practicing designers. The evaluation, conducted as part of the EU TOICA project, demonstrated the usefulness of the approach.
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    Multi-objective optimal longitudinal flight control system design for large flexible transport aircraft
    (IEEE, 2018-11-01) Song, Sipeng; Whidborne, James F.; Lone, Mudassir; Molina-Cristobal, Arturo
    This paper presents a multi-objective evolutionary algorithm design of a longitudinal optimal controller for a large flexible transport aircraft. The algorithm uses a mixed optimization approach based on a combination of Linear Quadratic Regulator (LQR) control and a Multi-Objective Genetic Algorithm (MOGA) to search over a set of possible weighting function structures and parameter values in order to satisfy a number of conflicting design criteria. The proposed approach offers a number of potential optimal solutions lying on or near the Pareto optimal front of competing objectives. The approach is explained in this paper and some results are presented.
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    A set-based approach for coordination of multi-level collaborative design studies
    (AIAA, 2020-01-05) Chen, Xin; Riaz, Atif; Guenov, Marin D.; Molina-Cristobal, Arturo
    Presented in this paper is a framework for design coordination of hierarchical (multi-level) design studies. The proposed framework utilizes margin management and set-based design principles for handling the challenges associated with vertical and horizontal design coordination. The former is based on flexible constraints/margins, while the latter is handled by intersecting feasible design spaces across different teams. The framework is demonstrated with an industrial test-case from the UK ATI APPROCONE (Advanced PROduct CONcept analysis Environment) project.
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    Set-based approach to passenger aircraft family design
    (American Institute of Aeronautics and Astronautics, 2016-09-13) Riaz, Atif; Guenov, Marin D.; Molina-Cristobal, Arturo
    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.
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    Towards automating the sizing process in conceptual (airframe) systems architecting
    (AIAA, 2018-01-13) Bile, Yogesh H.; Riaz, Atif; Guenov, Marin D.; Molina-Cristobal, Arturo
    Presented is a method for automated sizing of airframe systems, ultimately aiming to enable an efficient and interactive systems architecture evaluation process. The method takes as input the logical view of the system architecture. A source-sink approach combined with a Design Structure Matrix (DSM) sequencing algorithm is used to orchestrate the sequence of the sub-system sizing tasks. Bipartite graphs and a maximum matching algorithm are utilized to identify and construct the computational sizing workflows. A recursive algorithm, based on fundamental dimensions of additive physical quantities (e.g., weight, power, etc.) is employed to aggregate variables at the system level. The evaluation, based on representative test cases confirmed the correctness of the proposed method. The results also showed that the proposed approach overcomes certain limitations of existing methods and looks very promising as an initial systems architectural design enabler.