Development of an automated aircraft subsystem architecture generation and analysis tool

Judt, David M.; Lawson, Craig

doi:10.1108/ec-02-2014-0033

Cited by 13 publications

(10 citation statements)

References 22 publications

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“…45 To tackle the issue of flexibility in MDA (and flexible synthesis/representation of systems), an interesting technique is functional decomposition (FD). 46 It is commonly used for design synthesis, since it allows systems to be represented by their intended functions and actual behaviours. Hirtz et al 47 have constructed a functional basis of generic physical functions, through reconciling previous efforts.…”

Section: Flexibility and Scalability Of Disciplinary Analysis Tools Imentioning

confidence: 99%

Uncertainty-Based Design Optimization and Technology Evaluation: A Review

Roelofs

Vos

2018

2018 AIAA Aerospace Sciences Meeting

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Evaluation and assessment of novel technologies for aerospace applications is essential for business strategy and decision making regarding development efforts. Since technology is evaluated in the conceptual design phase and little is known about the technology, large uncertainty is present. This uncertainty needs to be accurately assessed and managed. To investigate the research efforts that have been performed to perform technology evaluation under uncertainty, a literature review was conducted, focusing on methods and modeling approaches to assign and quantify these uncertainties. It is found that probability theory is still the most popular theory for representing uncertainty. Polynomial Chaos Expansions and Stochastic Collocation methods are gaining popularity for propagating uncertainty through a modeling environment, but Monte Carlo Simulations are still widely used. Commonly, surrogate models are used to reduce computational effort. Other efforts focus on the use of multifidelity approaches to reduce computational effort when high-fidelity methods are required. Four issues that may need to be addressed in future research were identified.

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Section: Flexibility and Scalability Of Disciplinary Analysis Tools Imentioning

confidence: 99%

Uncertainty-Based Design Optimization and Technology Evaluation: A Review

Roelofs

Vos

2018

2018 AIAA Aerospace Sciences Meeting

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“…Evidently, other efforts have been made towards similar goals. Mostly, systems are described by functions/behaviors, leading to the topic of functional decomposition [5][6][7][8][9][10], which is mainly used in design synthesis. This allows automatic selection of components to fulfill certain requirements.…”

Section: Fig 1 Technology Evaluation and Selection Process [4]mentioning

confidence: 99%

“…This allows automatic selection of components to fulfill certain requirements. Additionally, representing a system in terms of its behavior instead of a certain fixed parameterization gains popularity in model-based systems engineering [6,[11][12][13][14], which may be attributed to the formalization of behavioral descriptions. While these allow for a structured approach to describe systems and enable automated design synthesis, they all rely on human specified functions, which effectively are only labels.…”

Section: Fig 1 Technology Evaluation and Selection Process [4]mentioning

confidence: 99%

Formalizing Technology Descriptions for Selection During Conceptual Design

Roelofs

Vos

2019

AIAA Scitech 2019 Forum

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actuator instead of hydraulic), to behaviors (e.g. a structural element doubling as electric conductor), and to entire systems (e.g. a fixed-wing aircraft as opposed to a helicopter). Previously, a review on technology selection [1] identified the following challenges with technology evaluation and selection: 1) The application of design tools is limited to a specific vehicle type, because the sizing method is fixed [2] 2) Flexibility and scalability of disciplinary analysis tools is lacking [2] 3) Parameterization of geometry proves challenging in a generalized sense (i.e. problem specific parameterizations are possible, but geometry parameterization that holds for any problem is challenging, at the least) 4) Modeling of technologies is usually avoided and replaced by impact factors 5) Extensive use of expert judgment raises challenges due to subjectivity, conservatism, overconfidence and lack of experts Additionally, from discussions with practitioners at Saab, the following challenges with technology selection in the conceptual design phase were identified: (i) non-performance metrics (e.g. the effect of improved human-machine interaction) need to be included, although prove difficult to define and quantify, (ii) technology descriptions are not yet meaningful, and cannot traverse from detailed to high-level descriptions, nor capture quantifiable effects and enabling fair comparison between technologies, (iii) finding the best technology portfolio without enumerating all possible combinations cannot yet be done objectively, (iv) the assessment of dependencies between technologies is too subjective, and (v) when uncertainty is quantified, decision making is impaired in case of wide uncertainty bands. Several conclusions can be drawn from these challenges. Metrics that are not quantifiable cannot be addressed, and hence, technologies affecting those have no meaning. Alternatively, additional analysis methods should be developed. Uncertainty should be associated with technology (and system) readiness level (both on impact and development time). Additionally, the amount of uncertainty should be limited or decision-making in the event of large uncertainty should be supported. Insight is more important at this stage than arriving at a most optimal result, hence preference is given to evaluating current possibilities, rather than performing optimization. Therefore, a structured and traceable solution to technology definition, evaluation and selection is sought. Conventionally, technology selection is performed by collecting technology TRL and IRL levels, describing their effects in an impact matrix and their compatibility in a Technology Compatibility Matrix (TCM). Such an approach was taken in the works by Amadori et al. [3, 4], who depict the process as in Figure 1. The data collection phase is essentially carried out completely using expert judgment, with limited traceability and objectivity.

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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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Development of an automated aircraft subsystem architecture generation and analysis tool

Cited by 13 publications

References 22 publications

Uncertainty-Based Design Optimization and Technology Evaluation: A Review

Uncertainty-Based Design Optimization and Technology Evaluation: A Review

Formalizing Technology Descriptions for Selection During Conceptual Design

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

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