Exploring Structural Patterns Across Evolved and Designed Systems: A Network Perspective

Our desire to deliver increased functionality while setting tighter operational and regulative boundaries has fueled a recent influx of highly-coupled systems. Nonetheless, our current capacity to successfully deliver them is still in its infancy. Understanding how such Designed systems are structured, along with how they compare to their naturally Evolved counterparts, can play an important role in bettering our capacity to do so. Based on this premise, the structural patterns underlying a wide range of seemingly unrelated systems is uncovered using tools from network science. By doing so, structural patterns emerge and are subsequently used to highlight both similarities and differences between the two classes of systems. With a focus on the Designed class, and assuming that increased structural variety fuels design uncertainty, it is shown that their adherence to statistical normality (i.e. expected vs. encountered patterns and statistical correlations between combinations of such patterns) is rather limited. Insight of this sort has both theoretical (context agnostic approaches are increasingly relevant within the domain of Systems Engineering, yet are rarely used) and practical (transferability of knowledge) implications.