NewSpace company Nitrexo collaborates with the European Space Agency (ESA) in initiatives to develop ground-breaking technologies in space engineering, particularly in the areas of artificial intelligence, miniature satellites, and model-based system engineering, with the aims of improving efficiencies and productivity, reducing costs, and sparking new innovations
The ESA has developed a method for automatically gathering and storing space mission data to build a knowledge base that would help improve the design and launch of new space missions. Such knowledge can also be used to enable the industry to meet the 400% forecasted growth in satellite demand between 2021 and 2030.
The mission data that the agency gathered previously lacked structure, organization, and uniformity in that they were stored in different documents and formats, making it hard for experts to easily find the information they needed.
To resolve this issue, ESA researchers assessed the use of Language Models in restructuring publicly accessible mission information. This led to the development of Knowledge Graph, a unified and structured database that serves as the centralized repository for all of the agency’s mission data. It uses GPT-3 (Generative Pre-Trained Transformer 3), a pre-trained Language Model that employs deep learning in the production of human-like text.
Future endeavours in this area include finding open-source models to replace GPT-3 and ensuring that the Knowledge Graph and the ESA Space System Ontology are aligned.
The development of miniaturized electronic equipment has paved the way for the development of smallsats or small satellites, which can weigh as light as 20 kgs. Truly game changers in the industry, they significantly reduce launch costs; thus, enabling the mass production of satellites.
The rise of smallsats has led to an increase in the number of nanosatellite constellation projects and to an endless number of applications, the most lucrative being its application in broadband connectivity. It has also led to the entry of many new players in the nano-satellite and mini-launch vehicle industry, though Arianespace and SpaceX remain the biggest companies in the field.
Model-based system engineering was developed to address the problems and inefficiencies that came with traditional system engineering, a document-based approach that can no longer effectively handle modern space systems. This is in light of such systems growing more complex and elaborate and where text descriptions are no longer enough to consistently and completely describe the systems.
The adoption of model-based system engineering makes data more accessible. It reduces the need for documentation, and it ensures that a space mission can continue digitally all through its life cycle, across disciplines, and throughout supply chains.
Instead of using documentation to build a project, model-based system engineering uses models to describe the various elements and subsystems in the project. It presents information in the form of tables, diagrams, and the like, which software applications and computers can more easily process. The models can also be continually tested against the customer’s changing needs, ensuring that they are met.
Model-based system engineering also provides a common design environment, which allows stakeholders across various systems and from different countries and organizations to easily collaborate.
A challenge posed by this ease of collaboration and information sharing is ensuring the security of sensitive information so that only the information that stakeholders are willing to share and can legally use are added as inputs to the models used.
Nitrexo’s development of its software platform, the Digital Engineer® , is geared towards meeting these knowledge sharing needs of the industry — creating a collaborative environment for experts as well as addressing the various challenges that the solution may bring.
Nitrexo’s software platform, the Digital Engineer®, is geared towards meeting these knowledge sharing needs of the industry. It organizes data, enabling engineers to search for information, as well as share their findings or any new knowledge gained. It also automates many engineering processes, which can speed up the development of new technologies.
The Digital Engineer® creates a collaborative environment that enables experts to quickly move forward with their projects as well as overcome any roadblocks that they may encounter
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