Speaker: Nicholas Battista, School of Science, College of New Jersey

Topic:  To fish, worms, and beyond: using computational models to study how variations in morphology and kinematics affect swimming performance

Abstract: From tunas to tunicates, the ocean is home to an incredible diversity of animals of many shapes and sizes. For all animals, living life and moving around in a liquid environment presents unique challenges that will vary based on the shape and size of the organism. Animals have evolved a variety of morphological structures, locomotor mechanisms, and swimming strategies that help reduce their energy expenditure by favoring more energetically efficient modes. Comprehensive studies that consider multiple morphological and kinematics traits and their influence on swimming performance are used to investigate these differing strategies. Experiments using live animals are common and provide important parameters, but they are limited and it may be unrealistic to find enough animals with desired characteristics to test across the landscape of multiple traits. Computational modeling provides a powerful tool that can bypass these constraints inherent in live animal experiments and help us gain insight into how morphological or kinematics changes affect performance across different scales. For example, computational modeling can quantitatively assess how natural variation affects performance and identify where trade-offs occur. In today's talk, I will describe our lab's approach to studying the swimming behaviors for a variety of animals through a blend of mathematical modeling, computational fluid dynamics, and machine learning. I will walk through our modeling process using Tomopteris, a polychaete, as an example, while also touching upon our own set of challenges, limitations, and future directions.