Search results1 – 2 of 2
This paper aims to describe the development of a knowledge management system (KMS) for the Nadir and Occultation for Mars Discovery (NOMAD) instrument on board the…
This paper aims to describe the development of a knowledge management system (KMS) for the Nadir and Occultation for Mars Discovery (NOMAD) instrument on board the ESA/Roscosmos 2016 ExoMars Trace Gas Orbiter (TGO) spacecraft. The KMS collects knowledge acquired during the engineering process that involved over 30 project partners. In addition to the documentation and technical data (explicit knowledge), a dedicated effort was made to collect the gained experience (tacit knowledge) that is crucial for the operational phase of the TGO mission and also for future projects. The system is now in service and provides valuable information for the scientists and engineers working with NOMAD.
The NOMAD KMS was built around six areas: official documentation, technical specifications and test results, lessons learned, management data (proposals, deliverables, progress reports and minutes of meetings), picture files and movie files. Today, the KMS contains 110 GB of data spread over 11,000 documents and more than 13,000 media files. A computer-aided design (CAD) library contains a model of the full instrument as well as exported sub-parts in different formats. A context search engine for both documents and media files was implemented.
The conceived KMS design is basic, flexible and very robust. It can be adapted to future projects of a similar size.
The paper provides practical guidelines on how to retain the knowledge from a larger aerospace project. The KMS tool presented here works offline, requires no maintenance and conforms to data protection standards.
This paper shows how knowledge management requirements for space missions can be fulfilled. The paper demonstrates how to transform the large collection of project data into a useful tool and how to address usability aspects.
This paper aims to describe the development of an advisory system that helps building sound finite element (FE) models from computer-aided design data, with actual…
This paper aims to describe the development of an advisory system that helps building sound finite element (FE) models from computer-aided design data, with actual uncertainty levels expressed by error values in per cent, as today there is no widely accepted tool for FE idealisation error control.
The goal is to provide a computer-aided engineering (CAE) environment which assists the FE modelling phase. A demonstration program has been developed that leads the user through a step-by-step process and helps to detect idealisation errors. Uncertainties are identified and analysed following the procedure. An example illustrates the methodology on the collapse analysis of aerospace stiffened panels.
The design shows how a knowledge-based system can be used to aid a safe virtual product development.
The extension of current CAE environments is difficult, as the programs do not provide sufficient flexibility, changeability and FE solver independence. New developments can take the presented concept as a starting point.
The application of error control strategies increases the FE modelling fidelity and can prevent incorrect design decisions. The practical conversion of FE idealisation support depends on the ambitions of CAE software providers.
This research shows how a previously paper-and-pencil-based error control procedure can be transformed to an easy-to-use tool in modern software.