How "digital twins" could help us predict the future | Karen Willcox
Nov 3, 2023
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Aerospace engineer Karen Willcox explores the incredible possibilities of 'digital twins' across engineering, climate studies, and medicine. She discusses the use of digital twins to understand and improve complex systems, personalized predictions, engineering systems, applications in various fields, and the challenges in creating digital twins.
Digital twins are virtual models that can predict how systems work and improve their design across various fields.
Combining personalized models and data assimilation allows digital twins to provide tailored predictions and recommendations for individuals.
Deep dives
The Potential of Digital Twins
Digital twins are virtual computer models of physical items that have the potential to predict how systems work and improve their design. They can be created for various objects, including cars, planes, buildings, forests, and landscapes. While digital twins are not yet functional for super-powered car chases, they can help us understand how things are built and make them better.
Personalized Models and Data Assimilation
The combination of personalized models and data assimilation is essential in creating digital twins. Devices like Fitbits and smartphones collect personalized data, which are then used with mathematical and statistical models to create personalized models. Data assimilation continuously updates the models as new data is collected, allowing the digital twin to adapt to the changing state of the system. This results in tailored predictions and recommendations for individuals.
Challenges and Applications of Digital Twins
Creating digital twins for complex systems is challenging due to the scales they cover and the limitations of data. Computational models that encompass all scales are computationally intractable, and data for complex systems are often sparse, noisy, and indirect. However, the combination of predictive physics-based models, machine learning, and high-performance computing offers hope for addressing these challenges. Digital twins have potential applications in aerospace engineering, civil infrastructure, energy efficiency, agriculture, and healthcare.
From health-tracking wearables to smartphones and beyond, data collection and computer modeling have become a ubiquitous part of everyday life. Advancements in these areas have given birth to "digital twins," or virtual models that evolve alongside real-world data. Aerospace engineer Karen Willcox explores the incredible possibilities these systems offer across engineering, climate studies and medicine, sharing how they could lead to personalized medicine, better decision-making and more.