G. la Rocca
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34 records found
1
Sub-scale flight test model design
Developments, challenges and opportunities
Growing interest in unconventional aircraft designs coupled with miniaturization of electronics and advancements in manufacturing techniques have revived the interest in the use of Sub-scale Flight Testing (SFT) to study the flight behaviour of full-scale aircraft in the early stages of design process by means of free-flying sub-scale models. SFT is particularly useful in the study of unconventional aircraft configurations as their behaviour cannot be reliably predicted based on legacy aircraft designs. In this paper, we survey the evolution of various design approaches (from 1848 to 2021) used to ensure similitude between a sub-scale model and its full-scale counterpart, which is an essential requirement to effectively perform SFT. Next, we present an exhaustive list of existing sub-scale models used in SFT and analyse the key trends in their design approaches, test-objectives, and applications. From this review, we conclude that the state-of-the-art sub-scale model design methods available in literature have not been used extensively in practice. Furthermore, we argue that one sub-scale model is not sufficient to predict the complete flight behaviour of a full-scale aircraft, but a catalog of tailored sub-scale models is needed to predict full-scale behaviour. An introduction to the development of such a catalog is presented in this paper, but the development of a formal methodology remains an open challenge. Establishing an approach to develop and use a SFT catalog of models to predict full-scale aircraft behaviour will help engineers enhance confidence on their designs and make SFT a viable and attractive testing method in the early stages of design.
Decisions regarding the system architecture are important and taken early in the design process, however suffer from large design spaces and expert bias. Systematic design space exploration techniques, like optimization, can be applied to system architecting. Realistic engineering benchmark problems are needed to enable development of optimization algorithms that can successfully solve these black-box, hierarchical, mixed-discrete, multi-objective architecture optimization problems. Such benchmark problems support the development of more capable optimization algorithms, more suitable methods for modeling system architecture design space, and educating engineers and other stakeholders on system architecture optimization in general. In this paper, an engine architecting benchmark problem is presented that exhibits all this behavior and is based on the open-source simulation tools pyCycle and OpenMDAO. Next to thermodynamic cycle analysis, the proposed benchmark problem includes modules for the estimation of engine weight, length, diameter, noise and NOx emissions. The problem is defined using modular interfaces, allowing to tune the complexity of the problem, by varying the number of design variables, objectives and constraints. The benchmark problem is validated by comparing to pyCycle example cases and existing engine performance data, and demonstrated using both a simple and a realistic problem formulation, solved using the multi-objective NSGA-II algorithm. It is shown that realistic results can be obtained, even though the design space is subject to hidden constraints due to the engine evaluation not converging for all design points. ...
Decisions regarding the system architecture are important and taken early in the design process, however suffer from large design spaces and expert bias. Systematic design space exploration techniques, like optimization, can be applied to system architecting. Realistic engineering benchmark problems are needed to enable development of optimization algorithms that can successfully solve these black-box, hierarchical, mixed-discrete, multi-objective architecture optimization problems. Such benchmark problems support the development of more capable optimization algorithms, more suitable methods for modeling system architecture design space, and educating engineers and other stakeholders on system architecture optimization in general. In this paper, an engine architecting benchmark problem is presented that exhibits all this behavior and is based on the open-source simulation tools pyCycle and OpenMDAO. Next to thermodynamic cycle analysis, the proposed benchmark problem includes modules for the estimation of engine weight, length, diameter, noise and NOx emissions. The problem is defined using modular interfaces, allowing to tune the complexity of the problem, by varying the number of design variables, objectives and constraints. The benchmark problem is validated by comparing to pyCycle example cases and existing engine performance data, and demonstrated using both a simple and a realistic problem formulation, solved using the multi-objective NSGA-II algorithm. It is shown that realistic results can be obtained, even though the design space is subject to hidden constraints due to the engine evaluation not converging for all design points.
After almost three decades of evolution, it is not yet possible to apply MDO in collaborative projects within large, heterogeneous and distributed teams of experts, whilst nowadays necessary for the development of any complex product. The H2020 project AGILE took the challenge of devising a novel paradigm to swiftly set up and deploy large distributed MDO systems, that are easy to (re)configure and monitor during the whole process, from requirements definition to data post-processing. The main outcome is an advanced set of tools and methods contributing to a 3rd generation MDO environment, specifically tailored to the aerospace industry. The AGILE paradigm is built on top of two main pillars, the so-called knowledge architecture and the collaborative architecture. The former, which is the main focus of this paper, provides a structured approach and the related workbench to formulate and inspect any automated design process, including fully formalized MDO systems. The latter includes the tools and methods to translate these formulations into executable workflows and deploy them across distributed networks. Although AGILE aims specifically at aircraft MDO, the proposed knowledge architecture provides a general conceptual framework that is suitable for the development of any complex product. The knowledge architecture has a multi-level hierarchical structure, consisting of four layers: development process, automated design, design competences and data schemas. Interfaces between the various layers are defined to achieve a fully.interconnected development process. This paper provides first a description of the knowledge architecture as a generalized paradigm to formulate collaborative and distributed MDO systems. Then, the specific implementation of such a paradigm within the AGILE project is illustrated: four knowledge architecture applications and two data schemas are described in detail. Finally, the whole approach is demonstrated by means of a realistic aircraft design case. This implementation proved successful in multiple aspects. First of all, in allowing heterogeneous teams of experts to generate complete and correct MDO system formulations involving large amount of distributed disciplinary tools, while maintaining full control and systematic overview of the complete system archi- tecture. Second, in offering the necessary agility to adjust and reconfigure the formulated MDO systems, such to support the iterative and evolutionary nature of their development process. Finally, by dramatically accelerating the setup time of the MDO system, thanks to the automation of the complex, lengthy and repetitive operations involved in the partitioning and coordination process, and to the effective support in inspecting and resolving the eventual inconsistencies in the data flow, arising every time tools are added or modified, or different solution strategies are implemented.
The research and innovation AGILE project has developed an approach, the so-called AGILE Paradigm, focusing on the acceleration of the deployment and operation of collaborative Multidisciplinary Design Analysis Optimization systems, which in turns can be exploited to accelerate the development of complex products, such as novel aerospace systems. Although the technologies developed for the implementation of the paradigm, have proved to reduce the deployment and operational time to more than 40% with respect to conventional MDAO approaches, the AGILE Paradigm has not been formalized and model by digital design engineering practices. This work introduces a novel approach leveraging MBSE principles to streamline the development of agile MDAO design systems, and establishing a bridge between MBSE and MDAO. Major outcomes here presented are the MBSE-driven models of the so-called AGILE MDAO system, representing the architecture, the requirements, as well as the organizational aspects, and all the interactions and activities implemented during the life-cycle stages of the MDAO system. The MBSE Architectural Framework, which defines the underlying ontological concepts and perspectives driving the development of the AGILE MDAO system model, are modeled and presented as well. The paper introduces for the first time the overall approach, as well as the high-level elements of the models developed, here represented by making use of SysML standard. The described approach is at the core of the recently launched project AGILE4.0, in which its scope will be expanded to cover the entire life-cycle of the development of complex aeronautical systems.
Alpha-SIM
A quick 3D geometry model simplification approach to support aircraft EWIS routing
Routing design of aircraft Electrical Wiring Interconnection System (EWIS) is time-consuming and error-prone. A solution, which automatically routes the EWIS inside the aircraft Digital MockUp (DMU), has been proposed and presented in the previous publications. The DMU, however, includes over-detailed features, which hardly influence the routing results but significantly increase the geometry-involved computational time thus hampering any automated routing. These features cannot be easily and efficiently suppressed. Therefore, a quick 3 D geometry simplification method, named Alpha-SIM, is proposed to enable a quick simplification of the airframe components included in the DMU and improve the benefit of the aforementioned automatic EWIS routing approach. The method is inspired by Descriptive Geometry techniques and the 3 D modelling approach using 2 D sketches, and aims at removing very detailed and/or internal features while preserving the intuitive notional shape of the given CAD model. The intuitive notional shape is represented by a 3 D point cloud of the model outer boundary and their 2 D projections on user-defined planes. These 2 D projections are then processed such to generate a set of 2 D profiles, called Alpha-Shapes, which are used, eventually, to re-build the 3 D model of the DMU components in a simplified/de-featured manner. By controlling the density of the 3 D points and the Alpha value to generate the 2 D profiles from the point projections, various geometric approximation levels can be achieved. The results of the test cases demonstrate the efficiency and effectiveness of the proposed method on the geometry simplification for automatic EWIS routing.
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Streamlining Cross-Organizational Aircraft Development
Results from the AGILE Project
The research and innovation AGILE project developed the next generation of aircraft Multidisciplinary Design and Optimization processes, which target significant reductions in aircraft development costs and time to market, leading to more cost-effective and greener aircraft solutions. The high level objective is the reduction of the lead time of 40% with respect to the current state-of-the-art. 19 industry, research and academia partners from Europe, Canada and Russia developed solutions to cope with the challenges of collaborative design and optimization of complex products. In order to accelerate the deployment of large-scale, collaborative multidisciplinary design and optimization (MDO), a novel methodology, the so-called AGILE Paradigm, has been developed. Furthermore, the AGILE project has developed and released a set of open technologies enabling the implementation of the AGILE Paradigm approach. The collection of all the technologies constitutes AGILE Framework, which has been deployed for the design and the optimization of multiple aircraft configurations. This paper focuses on the application of the AGILE Paradigm on seven novel aircraft configurations, proving the achievement of the project’s objectives. ...
The research and innovation AGILE project developed the next generation of aircraft Multidisciplinary Design and Optimization processes, which target significant reductions in aircraft development costs and time to market, leading to more cost-effective and greener aircraft solutions. The high level objective is the reduction of the lead time of 40% with respect to the current state-of-the-art. 19 industry, research and academia partners from Europe, Canada and Russia developed solutions to cope with the challenges of collaborative design and optimization of complex products. In order to accelerate the deployment of large-scale, collaborative multidisciplinary design and optimization (MDO), a novel methodology, the so-called AGILE Paradigm, has been developed. Furthermore, the AGILE project has developed and released a set of open technologies enabling the implementation of the AGILE Paradigm approach. The collection of all the technologies constitutes AGILE Framework, which has been deployed for the design and the optimization of multiple aircraft configurations. This paper focuses on the application of the AGILE Paradigm on seven novel aircraft configurations, proving the achievement of the project’s objectives.
Formulation and integration of MDAO systems for collaborative design
A graph-based methodological approach
This paper proposes a novel methodology and its software implementation, called KADMOS (Knowledge- and graph-based Agile Design for Multidisciplinary Optimization System), to increase the agility of design teams in collaborative Multidisciplinary Design Analysis and Optimization (MDAO). Agility here refers to the ease and flexibility to assemble, adjust and reconfigure MDAO computational systems. This is a necessary feature to comply with the complex and 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 proceeding with integration of the executable workflow. A thorough formulation of the system becomes essential when such system is built on the many contributions of large, heterogeneous design teams. KADMOS can automate the generation of such formulations through a graph-based methodological approach. The graph syntax and manipulation algorithms form the core content of this paper. First, a simple MDAO benchmark problem is used to illustrate KADMOS's working principles. Second, a wing aerostructural design case is discussed to demonstrate KADMOS's capabilities to enable collaborative MDAO on large problems of industry-representative complexity. Next to its graph-theoretic foundation, KADMOS makes use of two data schemas: one containing the parametric representation of the product being designed and a second to store the achieved formulation of the MDAO system. The latter enables the interchangeable use of different process integration and design optimization platforms to automatically integrate the generated MDAO system formulation as an executable workflow. The proposed approach has been estimated to be capable of halving the time typically required to set up and iteratively reconfigure a complex MDAO system, while allowing discipline experts and system architects to maintain constant oversight and control of the overall system and its components by means of human-readable dynamic visualizations.
A new system is presented that enables the visualization of large multidisciplinary design optimization (MDO) problems and their solution strategy. It was developed within the scope of the European project AGILE. In AGILE, collaborative MDO is performed in large, heterogeneous teams of experts by solving MDO problems using a collection of design and analysis tools. This paper focuses on the visualizations required to support the formulation phase of an MDO project. The Knowledge and graph-based AGILE Design for Multidisciplinary Optimization System (KADMOS), an open-source MDO support system developed by Delft University of Technology, uses graph-based analysis to formulate an MDO problem and its solution strategy, based on the disciplinary analyses available in a repository. The results of KADMOS are stored in the standardized format CMDOWS (Common MDO Workflow Schema), which comprises the entire information on an MDO system. Although, based on Extensible Markup Language, the readability of the CMDOWS file is quite poor also for MDO experts, especially for large MDO systems involving thousands of variables. Providing visualization capabilities to thoroughly inspect the outcome of the different MDO formulation steps becomes a key factor to enable the specification of large MDO systems in a heterogeneous team. Therefore, VISTOMS (VISualization TOol for MDO Systems), a dynamic visualization package, was developed by RWTH Aachen University to enable the visualization and inspection of the different MDO system specification steps, thereby removing one of the main hurdles for using MDO as a development process. The developed visualization capabilities are demonstrated by means of an aerostructural wing design optimization project.
This paper presents a critical discussion on the automated problem formulation and workflow creation approach developed within the European project AGILE to support and accelerate the setup of aircraft MDO workflows in a large, heterogeneous team of experts. The developed framework is based on a methodological approach, called the AGILE paradigm, where a complete MDO system is formulated and executed in five main steps. In Step I the requirements are collected, in Step II a repository of disciplinary tools is established, in Step III the design optimization problem is formulated and structured according to a selected MDO architecture, in Step IV an executable workflow is assembled and finally operated in Step V. All steps have been streamlined and highly automated through the development of a novel set of MDO support applications and data standards, addressed as the AGILE MDO framework. This framework was tested through a series of design campaigns culminating with four design tasks, where a variety of unconventional aircraft configurations is collaboratively designed using MDO. After a brief introduction on the AGILE paradigm and the four design tasks, this paper will focus on a set of AGILE framework core components enabling the automated process to formulate and execute collaborative MDO systems. The strengths and current limitations of these components are discussed, based on the extensive feedback from the heterogeneous set of specialists involved in the four design tasks. Although drastic reductions in the setup time of an MDO system (up to 40 percent) appear to be already achievable, recommendations are provided to improve the flexibility, usability and scalability of the framework.