Composing MDAO symphonies: graph-based generation and manipulation of large multidisciplinary systems

Abstract

This paper proposes a novel methodology and its software implementation, called KAD-MOS (Knowledge-and graph-based Agile Design for Multidisciplinary Optimization System), which aims at increasing the agility of aircraft design teams that perform collaborative multidisciplinary design analysis and optimization (MDAO) by means of graph manipulation techniques. By agility, the ease and flexibility to assemble, adapt and adjust MDAO computational systems is intended here, as necessary to better fit the iterative nature of the aircraft design process. KADMOS has been developed on the notion that a formal specification of an MDAO system is required before its actual implementation, especially to be able to compose large and complex systems in multidisciplinary design teams. This specification system is under development as part of the EU project AGILE where a new generation of aircraft MDAO systems is investigated to support collaboration of heterogeneous teams of experts. KADMOS improves the agility of the design team in three ways: 1) reducing the setup time required to compose large and complex MDAO models, 2) enabling the systematic inspection and debugging of this model, and 3) manipulating the model for automated creation and reconfiguration of optimization strategies, including the accompanying executable workflow. This is achieved by means of a graph-based analysis system that combines different existing advantageous techniques for performing MDAO, such as the use of a single shared data schema containing a parametric representation of the aircraft, knowledge-based technologies, and simulation workflow (SWF) software packages. Two MDAO case studies will be presented in the paper. The first case study is based on a simple analytical problem, generally used in literature for MDAO benchmarking studies. The second case study concerns a detailed wing aerostructure design using a collection of wing design tools. While the simple and compact analytical problem is used in this paper to demonstrate the functionalities of the tool, the wing design case demonstrates the capability of KADMOS to support quick formulation, (re)configuration, and execution of MDAO workflows using distributed and heterogeneous sets of analysis tools.

Graph-based algorithms and data-driven documents for formulation and visualization of large MDO systems

“…KADMOS' functionalities are briefly explained in Sect. 2.2, while detailed information can be found in another publication [12]. As illustrated in Fig.…”

“…The ability of KADMOS to support the specification of the MDO system is discussed in detail in earlier work [12]. A mapping between the three stages of the formulation phase in Fig.…”

A clustered and surrogate-based MDA use case for MDO scenarios in AGILE project

“…The full AGILE knowledge architecture is discussed in [16]. Here, three elements of the architecture have been used to support the creation of the different surrogate models and optimization workflows: the graph-based MDO formulation system KADMOS (Knowledge-and graph-based Agile Design for Multidisciplinary Optimization System) [26], the visualization tool for MDO systems VISTOMS (VISualization TOol for MDO Systems) [27], and the data standard to store multidisciplinary system formulations CMDOWS (Common MDO Workflow Schema) [28].…”

“…For the IDF formulation, that requires coupling variables as design variables, a range had to be defined in line with the one used in the cluster DOEs. Starting from [27] with KADMOS [26]. Eventually, CMDOWS [28] files of the MDO solution strategy (see Figure 8) were automatically created.…”

WESgraph: a graph database for the wind farm domain

“…However, at the current stage of development of the domain, during which subsystems such as turbines have already seen a good number of optimized design iterations, the system interactions have become relatively more important. This prompts a more holistic, systems engineering approach to open up the possibility of further gains in, e.g., productivity, efficiency, and robustness (van Kuik et al, 2016). Therefore, a tool that enables a developer, designer, or researcher in the field to keep the overview can provide great benefits.…”