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DLR's Remote Component Environment (RCE) is an open-source software environment for defining and executing workflows containing distributed simulation tools by integrating them into a peer-to-peer network. It is being developed primarily by DLR and has been used in various engineering projects, including several aerospace projects dealing with multidisciplinary optimization (MDO) and multidisciplinary analysis (MDA). RCE has several advantages that can help to achieve more reusable multidisciplinary processes. The workflow is composed of built-in and user-defined components. Disciplinary tools are integrated as standalone components, with defined inputs and outputs, and then distributed over the network. While executing the workflow, data dependencies between the components are automatically detected, and a component is executed as soon as all its input data is available. Thus, multiple components can run at the same time. The components of a multidisciplinary process can also be executed in a distributed manner, where the tools are located on different machines with possibly different operating systems. Once configured, the peer-to-peer network is automatically established between the RCE instances running on different machines, making components visible and executable even between instances that are only connected indirectly. The distributed execution capability alleviates tool deployment issues, including those related to the protection of intellectual property. RCE supplies a graphical editor for creation of workflows, using the built-in components to control the data flow. Some built-in components can be used to perform optimization tasks within the workflow, including nested loops, using built-in or user integrated optimization algorithms. We demonstrate the use of some of the key features of RCE for MDA and MDO purposes based on several collaborative DLR projects where distributed simulation tools are being used.

Covering all relevant physical effects and mutual influences during aircraft preliminary design at a sufficient level of fidelity necessitates simultaneous consideration of a large number of disciplines. This requires an approach in which teams of engineers apply their analysis tools and knowledge to collaboratively approach design challenges.