Meeting Abstract
Biologists have long understood the importance of variation in evolution. Variation provides the raw materials on which natural selection acts, leading to potentially important differences in functional performance. Varying parameters in complex, functional systems can lead to unpredictable effects on the performance of such systems, displaying synergy (effects of more than sum of the changes alone) or many-to-one mapping/mechanical equivalence (many parameter combinations result in similar performance). Understanding how simultaneous variation in parameters impacts the performance of a system is key to understanding how natural selection has shaped these functional systems over time. In this study, we take a simplified version of a very complex functional system (circulatory flow driven by a peristaltic heart) and subject it to uncertainty analysis, a set of mathematical techniques that assess the uncertainty in complex, physical systems. We use uncertainty quantification and sensitivity analysis through generalized polynomial chaos expansion to simultaneously assess the impact of variation in three main parameters of this model. Through this analysis, we quickly and efficiently distinguish sensitive parameters (compression ratio of the tube) over relatively insensitive parameters (Womersley number, compression frequency) through the use of Sobol indices. We also extend the interpretation of the sensitivity analysis to make predictions about the variance of these parameters in living animals: sensitive parameters being highly conserved versus insensitive parameters being free to diversify.
