Methodology for Automated Aircraft Systems Architecture Enumeration and Analysis

Judt, David M.; Lawson, Craig

doi:10.2514/6.2012-5648

Cited by 7 publications

(11 citation statements)

References 3 publications

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“…This semantic reasoning is necessary for enabling systematic design space exploration, however it generally does not offer the formalization required for generating, evaluating, and exploring system architectures automatically, as needed for systematic design space exploration. More formalized approaches include methods based on the morphological matrix [4,5], the Architecture Decision Graph [6], and function-form mapping [7,8]. Important features for enabling systematic exploration is the explicit identification and tracking of architecting decisions, and enabling automated quantitative analysis of architecture candidates.…”

Section: Introductionmentioning

confidence: 99%

System Architecture Design Space Exploration: An Approach to Modeling and Optimization

Bussemaker

Ciampa

Nagel

2020

Aiaa Aviation 2020 Forum

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Systematic modeling of architecture design spaces is needed when architecting complex systems, to support experts in making less biased decisions, and to formulate the optimization problem needed to explore the large combinatorial design space. Existing methods do not offer enough compatibility with the Model-Based Systems Engineering (MBSE) approaches, cannot model all needed design scenarios, or are not flexible enough when it comes to architecture evaluation. A new method is presented that provides a semantic representation of the architecture design space, modeled as the Architecture Design Space Graph (ADSG). The ADSG represents three types of architectural decisions: function-component mapping, component characterization, and component connection. The ADSG is constructed from a design space definition, and discrete architectural decisions are automatically inserted according to specified rules. Once decisions and metrics have been defined, the hierarchical, mixed-integer, multi-objective optimization problem can be formulated: decisions are mapped to design variables, and performance metrics are mapped to objectives or constraints. An application of the method to the Apollo mission architecting problem is presented. Nomenclature

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Section: Introductionmentioning

confidence: 99%

System Architecture Design Space Exploration: An Approach to Modeling and Optimization

Bussemaker

Ciampa

Nagel

2020

Aiaa Aviation 2020 Forum

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“…The aircraft's new sizes further influence the subsystems results, leading to an iterative process. Judt and Lawson's approach [10], [11], utilize a methodology that generates the full enumeration of architectures given a function tree. This function tree consists on the aircraft functions (boundary functions), for which one or more candidate solutions are proposed, which in turn induce more functions which can be satisfied by different solutions, inducing more functions and so forth.…”

Section: Introductionmentioning

confidence: 99%

Enabling Interactive Safety and Performance Trade-offs in Early Airframe Systems Design

Jimeno

Riaz

Guenov

et al. 2020

AIAA Scitech 2020 Forum

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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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“…These functional requirements are general enough to be linked to various physical component models, making up the architecture concept. Such a process, combined with an intelligent framework, of component filtering, functional reconfiguration and input/output (I/O) variable linkages, is flexible enough to allow the consideration of a diverse range of architecture types ( Judt and Lawson, 2012). Combined with model-based approaches and moving away from empirical methods, an extended design space is available.…”

Section: Introductionmentioning

confidence: 99%

Development of an automated aircraft subsystem architecture generation and analysis tool

Judt

Lawson

2016

Engineering Computations

Self Cite

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Purpose-The work presents a new computational framework to address future preliminary design needs for aircraft subsystems. The ability to investigate multiple candidate technologies forming subsystem architectures is enabled with the provision of automated architecture generation, analysis and optimization. Main focus lies with a demonstration of the frameworks workings, as well as the optimizer's performance with a typical form of application problem. Design/methodology/approach-The core aspects involve a functional decomposition, coupled with a synergistic mission performance analysis on the aircraft, architecture, and component levels. This may be followed by a complete enumeration of architectures, combined with a user defined technology filtering and concept ranking procedure. In addition, a hybrid heuristic optimizer, based on ant systems optimization and a genetic algorithm, is employed to produce optimal architectures in both component composition and design parameters. The optimizer is tested on a generic architecture design problem combined with modified Griewank and parabolic functions for the continuous space. Findings-Insights from the generalized application problem show consistent rediscovery of the optimal architectures with the optimizer, as compared to a full problem enumeration. In addition multi objective optimization reveals a Pareto front with differences in component composition as well as continuous parameters. Research Limitations-This paper demonstrates the frameworks application on a generalized test problem only. Further publication will consider real engineering design problems. Originality/Value-The paper addresses the need for future conceptual design methods of complex systems to consider a mixed concept space of both discrete and continuous nature via automated methods.

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Methodology for Automated Aircraft Systems Architecture Enumeration and Analysis

Cited by 7 publications

References 3 publications

System Architecture Design Space Exploration: An Approach to Modeling and Optimization

System Architecture Design Space Exploration: An Approach to Modeling and Optimization

Enabling Interactive Safety and Performance Trade-offs in Early Airframe Systems Design

Development of an automated aircraft subsystem architecture generation and analysis tool

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