1. Introduction & background
Designing an aircraft is a very complex engineering task. The complexity needs to be handled by decomposition, using a hierarchy of different levels. In general, the aircraft design process is divided into three phases: the conceptual design phase, the preliminary design phase and the detailed design phase. The product fidelity, the model complexity and the time needed for the design process increase exponentially from the previous phase to the next one.
In the conceptual design phase, the aircraft is defined at a system level. Many variants are studied, and the design selected is the one that best fulfills the mission to the specifications of the market or a customer. This determines a general aircraft configuration capable of performing its mission, together with first sizing estimates. In the preliminary design phase, the central challenge is to perform design optimization in a distributed environment made up of distinct disciplinary design teams with individual solution strategies, locally defined variables and constraints, potentially costly computational analyses and interdisciplinary coupling. A variety of multidisciplinary design optimization (MDO) methods have been developed that enable a formalized design optimization process in the preliminary design phase. Figure 1 indicates the major design process of the conceptual and early preliminary design work leading up to freezing the configuration, starting wind tunnel testing and then continuing to advance the preliminary design.
The methods used differ from each other in how they handle local feasibility, interdisciplinary compatibility and local design autonomy. One such method is collaborative optimization. The detailed design phase includes the manufacturing details, the detailed definitions of the product and performance data as well as all other required product information. The earliest design process is a crucial stage, which commits up to 80 per cent of the life-cycle cost. But the actual cost is incurred much later (Zhang, 2015), as many of the decisions taken in this phase are made with a great deal of uncertainty. Improvements in this design stage offer the greatest scope for innovation, and for this reason we focus on bringing more fidelity into the early design steps to reduce the uncertainty. In the SciTech 2015 Conference in Kissimmee, the keynote speech on January 5, 2015 with title “Technology Roadmaps Pave the Way to Our Future” spelled out that “the potential of making more use of computational fluid dynamics (CFD) in the conceptual design [...]” could be especially useful for unconventional and innovative configurations.
In this paper, we will focus on the early design stages, i.e. the conceptual design as well as the preliminary design, and explore ways to improve the prediction fifidelity in these stages.
1.1 Data-centric scheme CPACS and workflflow manager RCE
As discussed earlier in the text, aircraft design requires severaldifferent design groups (each having their own focus) that need to exchange large amounts of data obtained from their analysis procedures and models. Managing the interconnections is complex and error-prone.
Adoption of a standardized, data-centric scheme for storage of all data improves consistency and reduces risks of misconceptions and errors in the process. It however requires an initial effort to make interfaces between analysis modules and the data archive. The Common Parametric Aircraft Configuration Schema (CPACS) (CPACS – A Common Language for Aircraft Design, 2015; CPACS Documentation, 2015), developed by Deutschen Zentrums für Luft- und Raumfahrt (DLR), was adopted for the New CEASIOM framework, and is described in the following section. A design loop runs several analysis modules in sequence. The remote component environment (RCE) integration environment and workflow manager records the sequence and manages the data transport and translation as well as logging the process. RCE, developed by DLR, makes it easy to set up and run a workflow also using modules in which the engineers are not discipline-experts.
1.2 Aerodynamic table for flight simulation
For the stability and control analysis as well as for the flight simulation, a large look-up table for aerodynamic forces and moments needs to be generated. There are different table/input formats required by different flight analysis tools. For example, the simulation and dynamic stability analyzer (SDSA) (Goetzendorf-Grabowski et al., 2011) developed by Warsaw University of Technology requires a set of three-dimensional tables of force and moment coefficients with the standard three-channel control systems. Details of the table format and its applications can be found in Zhang (2015).
In the results discussed in this paper, all the aero-data are saved in CPACS. Table I shows the aerodata format defifined in CPACS XML fifile. The force and moment coeffificients are recorded in body-axes as cf and cm, aligning with x-, y- or z directions. The tables are four-dimensional with independent variables machNumber (Ma), reynoldsNumber (Re), angleOfYaw (b ) and angleOfAttack (a). The dependence on rotation rates and control surface deflections are represented by dynamic and control derivatives, also recorded in fourdimensional tables. Detailed definitions can be found in CPACS Documentation (2015).
2. CEASIOM history and current status
The CEASIOM software framework for conceptualpreliminary design was created in the SimSAC – Simulating Aircraft Stability and Control Characteristics for Use in Conceptual Design – EU Framework 6 project. Its mission was to develop an integrated simulation environment to compute stability and control information with a quantifiable uncertainty. The resulting CEASIOM-100 tool programmed in MATLAB brought variable fidelity simulation to the conceptual-preliminary design process. CEASIOM-v4.0 is the latest version with each module up-to-date and is freely available from the CEASIOM website (www.ceasiom.com).
CEASIOM is a framework system that integrates disciplinespecific tools such as computer-aided design (CAD), mesh generation, CFD, stability and control analysis, and structural analysis, all for the purpose of aircraft conceptual design (Zhang, 2015).
A new CEASIOM version is under development in the EU Project AGILE (www.agile-project.eu), by adopting the CPACS XML data-format for representation of all design data pertaining to the aircraft under development. All the CEASIOM modules will be integrated in the RCE framework because it provides special extensions suitable for optimization.
With all the analysis modules integrated in RCE, a complete workflow from can be set up starting from the CPACS aircraft configuration (obtained from e.g. overall design stage) until stability and control assessment and flight performance. During this process, data from the variable-fidelity aerodynamic analysis tools are created, compiled and fused into a coherent aero-data set. In this paper, we will present the new CEASIOM functionalities by running such an exercise using the DC1 aircraft from the AGILE project (see also further below) (Figure 2).
2.1 Geometry – CPACSupdater
The aircraft geometry for the “old” CEASIOM was defined as a CEASIOM type XML file, which came from QCARD system built by Isikveren (2002) in his PhD dissertation. The New CEASIOM adopts the CPACS format, and all the aircraft geometries are defined in CPACS. The CPACS aircraft definition will be handled in module CPACSupdater within New CEASIOM.
It is extremely difficult to correctly parametrize an aircraft defined in CPACS XML file without visual feedback. The CPACSupdater, based on the old CPACScreator, is a Matlab program which works as a robust XML visual editor by parsing and transforming the XML file into the Matlab structure. The aircraft can be viewed, modified and updated smoothly, not only its external shapes and components but also its sub-components such as flaps and leading/trailing edge devices (TED) and its internal structures such as ribs, spars and fuel tanks. The updated aircraft definition is saved as a CPACS file for further use, ready to be delivered to other modules inside CEASIOM or to other external tools that are able to read the CPACS file format.
The CPACSupdater is a continuous work based on CPACScreator (Zhang, 2013), with algorithmic corrections and bugs-fixing. It is a pure geometry definition updater that computes the necessary geometric parameters calculated, such as the mass distributions and weight and balance information (under-development).
Figure 3 shows the main Graphic User Interface (GUI) of CPACSupdater that can be used to view, add, remove or modify a CPACS aircraft geometry definition. It contains two parts, the left part is the User Control Panel consisting all components, subcomponents, their parameters and user actions. The right part is the instant graphic feedback which responses to the user actions made in the User Control Panel.
Currently, three sub-components are supported by CPACSupdater: TED; a set of spars and ribs (defined as one sub-component); and fuel tanks. The sub-components transformations and symmetry parameters are defined by their parent component and shared with all its sub-components. Figure 4(a) and (b) shows the GUI to modify the TED and sets of ribs and spars, respectively...