The nervous system and body of Caenorhabditis elegans together constitute one of the best-characterized biological systems, yet the interaction between neural activity, biomechanics, and behavior remains incompletely understood. This project develops an integrated computational framework that combines detailed biomechanical simulation with connectome-scale neuronal modelling to investigate how neural activity gives rise to whole-animal behavior. The project couples the SOFA Framework for physically realistic simulation of the worm's deformable body with NEURON for biophysically grounded simulation of the neuronal connectome. Rather than treating neural dynamics and body mechanics independently, the framework models bidirectional interactions between the nervous system, muscles, body deformation, and environmental contact. This enables investigation of locomotion, sensory responses, and behavioral adaptation under varying mechanical and physiological conditions. A major challenge is the computational cost of these simulations. Mechanical simulations require millisecond-scale integration to accurately resolve body deformation and contact dynamics, while biologically relevant behaviors occur over time scales of tens of seconds to several minutes. Current prototype simulations execute on a laptop at approximately 2–3 simulation steps per second using a 1 ms timestep, making a single minute of simulated behavior require many hours of computation. Scientific studies further require repeated simulations for parameter optimization, sensitivity analyses, model validation, and exploration of alternative hypotheses. The Arrhenius CPU resource is well suited to these workloads. Both SOFA and NEURON are designed for CPU-based parallel execution, allowing multiple simulation campaigns to execute concurrently while maintaining reproducibility and efficient utilization of multicore nodes. The requested allocation will enable systematic exploration of the coupled neuromechanical model, supporting the development and validation of a predictive digital model of C. elegans behaviour. The resulting simulation platform will provide a computational resource for investigating how neural circuits, biomechanics, and environmental interactions collectively generate behavior, with applications ranging from basic neuroscience and biophysics to biologically inspired robotics and computational modelling.