Chitnelawong Pheerawich, Klishin Andrei A, Mackay Norman, Singer David J, van Anders Greg
Department of Physics, Engineering Physics, and Astronomy, Queen's University, Kingston, ON, K7L 3N6, Canada.
Department of Mechanical Engineering, University of Washington, Seattle, WA, 98195, USA.
Sci Rep. 2024 Jun 4;14(1):12789. doi: 10.1038/s41598-024-63278-3.
Emergent design failures are ubiquitous in complex systems, and often arise when system elements cluster. Approaches to systematically reduce clustering could improve a design's resilience, but reducing clustering is difficult if it is driven by collective interactions among design elements. Here, we use techniques from statistical physics to identify mechanisms by which spatial clusters of design elements emerge in complex systems modelled by heterogeneous networks. We find that, in addition to naive, attraction-driven clustering, heterogeneous networks can exhibit emergent, repulsion-driven clustering. We draw quantitative connections between our results on a model system in naval engineering to entropy-driven phenomena in nanoscale self-assembly, and give a general argument that the clustering phenomena we observe should arise in many distributed systems. We identify circumstances under which generic design problems will exhibit trade-offs between clustering and uncertainty in design objectives, and we present a framework to identify and quantify trade-offs to manage clustering vulnerabilities.
紧急设计故障在复杂系统中普遍存在，并且常常在系统元素聚集时出现。系统地减少聚集的方法可以提高设计的弹性，但是如果聚集是由设计元素之间的集体相互作用驱动的，那么减少聚集就很困难。在这里，我们使用统计物理学的技术来识别在由异构网络建模的复杂系统中设计元素的空间簇出现的机制。我们发现，除了单纯的、吸引驱动的聚集之外，异构网络还可以表现出涌现的、排斥驱动的聚集。我们在海军工程中的一个模型系统上的结果与纳米级自组装中熵驱动的现象之间建立了定量联系，并给出了一个一般性的论点，即我们观察到的聚集现象应该出现在许多分布式系统中。我们确定了在哪些情况下一般设计问题会在聚集和设计目标的不确定性之间表现出权衡，并且我们提出了一个框架来识别和量化权衡，以管理聚集漏洞。
