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Design Engineering Assistant for the Early Design of Space Missions – ICE Lab

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Summary: Space missions development takes years and traditionally starts with a feasibility study phase where experts consider several design options, trade-offs and eventually take decisions that will impact the rest of the mission life cycle. To make these first design decisions, experts rely both on their implicit knowledge (i.e. The former type of knowledge represents a substantial amount of unstructured data, which is today underutilized and too time-consuming to explore during the limited timeframe of a feasibility study. A solution is to design an Expert System (ES) to support the initial study input estimation, assist experts by answering queries related to previous design decisions or push them to explore new design options. Such an effort is led since January 2018 by two PhD students, Audrey Berquand and Francesco Murdaca, at the University of Strathclyde within the Intelligent Computational Engineering (ICE) lab, under the supervision of Dr. Annalisa Riccardi.


How Artificial intelligence Is Changing 3D Printing - GrabCAD Blog

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And let's face it, we subtly see it in our everyday lives when a form gets filled out, or a choice of books and movies is set up for us, by learning our past preferences. We further see it with new applications like voice activation, preset GPS directions, and many other applications. Artificial intelligence has gained recognition as a valuable tool to turbocharge so many applications in business, industry, and other corners of commerce. Remarkable outcomes using artificial intelligence are instilling positive and monumental changes in engineering design, and improved living for many throughout the world. In a parallel rhythm, 3D printing has emerged and continues to advance.


Semantics for Digital Engineering Archives Supporting Engineering Design Education

AI Magazine

This article introduces the challenge of digital preservation in the area of engineering design and manufacturing and presents a methodology to apply knowledge representation and semantic techniques to develop Digital Engineering Archives. This work is part of an ongoing, multiuniversity, effort to create cyber infrastructure-based engineering repositories for undergraduates (CIBER-U) to support engineering design education. The technical approach is to use knowledge representation techniques to create formal models of engineering data elements, workflows and processes. With these formal engineering knowledge and processes can be captured and preserved with some guarantee of long-term interpretability.


The 5 Biggest Technology Trends Disrupting Engineering And Design In 2020

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The way products are designed and engineered is changing thanks to new technologies. These technologies, from digital twins to 3D printing, not only support humans in their design and engineering work, but they can also efficiently uncover new ways of solving problems that humans hadn't thought of before. The human professionals in design and engineering roles in organizations will see changes to their job duties, will be challenged to acquire new skills and flexibility, and learn new ways of collaborating with machines. They also need to learn how to work with new design, engineering, and product development tools enabled by these new technologies. Organizations and professionals in engineering and design roles can't ignore the changes if they want to remain competitive.


Data-Driven Design-by-Analogy: State of the Art and Future Directions

arXiv.org Artificial Intelligence

Design-by-Analogy (DbA) is a design methodology, wherein new solutions are generated in a target domain based on inspiration drawn from a source domain through cross-domain analogical reasoning [1, 2, 3]. DbA is an active research area in engineering design and various methods and tools have been proposed to support the implement of its process [4, 5, 6, 7, 8]. Studies have shown that DbA can help designers mitigate design fixation [9] and improve design ideation outcomes [10]. Fig.1 presents an example of DbA applications [11]. This case aims to solve an engineering design problem: How might we rectify the loud sonic boom generated when trains travel at high speeds through tunnels in atmospheric conditions [11, 12]? For potential design solutions to this problem, engineers explored structures in other design fields than trains or in the nature that effectively "break" the sonic-boom effect. When looking into the nature, engineers discovered that kingfisher birds could slice through the air and dive into the water at extremely high speeds to catch prey while barely making a splash. By analogy, engineers re-designed the train's front-end nose to mimic the geometry of the kingfisher's beak. This analogical design reduced noise and eliminated tunnel booms.