Costly and unexpected stress fatigue breakdowns indicate a broader Air Force (AF) need for improved predictive analytics technology. Digital twin technology has emerged as an AF research area of interest, predominantly in manufacturing and maintenance use cases. However, the AF faces multiple other threats and challenges that could benefit from digital twin technology. The Peopleâs Republic of China plans to launch a Digital Yuan by the end of 2020, which it can weaponize to disrupt AF supply chains by freezing assets and manipulating markets. The AF needs a tool to monitor and wargame the Digital Yuanâs capabilities to fully understand the threat. In August 2020 the DOJ apprehended $2MM worth of cryptocurrency from ISIS, al-Qaeda, and Hamas that could have been used to finance terror attacks against AF installations; digital twin simulations could help investigators simulate and identify this sooner. In the cyber and space realm, the AF Missile Systems Center built the SatSim digital twin to wargame hacks against the Block IIR GPS satellite to better understand enemy cyber threats. With these diverse and nuanced examples, a clear need for a customizable and versatile AF digital twin analytics platform exists. BlockScienceâs cadCAD (complex adaptive dynamics Computer-Aided Design) is a cutting edge digital twin analytics platform (DTAP) that addresses diverse AF needs for digital twin predictive analytics and simulations. The first-of-its-kind cadCAD framework creates a digital proving ground where end-users create full-scale digital versions of real-world objects, processes, and digital assets so the AF can simulate and model scenarios and save time, money, and Airmen lives. cadCADâs early use was as an economic modeling simulator, having the distinction of being one of the worldâs first fully customizable cryptocurrency ecosystem simulation frameworks. The framework was created as an open-source template for modeling complex systems, such as digital currencies, designed for systems engineers, economists, capital markets traders, and other behavioral specialists to build upon using any combination of proprietary and commercial, off-the-shelf augmenting technologies. cadCAD is built as part of the scientific Python ecosystem. It seamlessly integrates with open-source proprietary data science computing stacks and enables continuous improvement with real-world feedback. cadCAD uses the Python programming language used by most data scientists globally and provides extensive scientific computation and data visua
