Research Areas

Simulation of Ships and Underwater Vehicles

Predicting how a ship or submarine moves — its performance, maneuvering characteristics, and safe operating limits — requires simulation tools that are both physically accurate and computationally tractable. ACIC has spent over two decades developing and applying the CFD methods that feed into these tools.

Our work includes six degree-of-freedom (6-DOF) maneuvering simulation, hydrodynamic coefficient generation for real-time simulation environments such as DSSP, reduced-order model (ROM) development, and studies of extreme maneuvering conditions including rising stability, free-surface effects, and submarine-surface ship interactions. More recently, ACIC has integrated machine learning surrogate models into these workflows to accelerate full-configuration simulations that would otherwise be computationally prohibitive.

Key methods: 6-DOF URANS and LES, wall-modelled LES (WMLES), detached eddy simulation (DES), reduced-order modelling, ML surrogate models, captive model simulations, free-surface modelling.

Ocean Mapping and Regional Ocean Modelling

Working with UNB's Ocean Mapping Group, ACIC develops methods for translating ocean floor survey data into fluid dynamic models and interactive digital twin environments. This involves processing sonar-derived bathymetry for CFD analysis, building models of underwater environments for vehicle simulation and mission planning, and creating systems that combine observational data with physics-based computation to support real-time decision-making.

Key methods: Sonar data processing, bathymetric modelling, CFD integration, digital twin development, data assimilation.

HPC Physics and Edge Data Assimilation

Physics-based simulation becomes most powerful when it can incorporate live or near-real-time data from the systems being modelled. ACIC develops workflows that combine large-scale HPC computation with data from IoT sensors and edge computing devices, enabling models to be continuously updated and deployed in environments where traditional cloud-only approaches are impractical.

This capability underpins Stage², ACIC's workflow orchestration platform, which manages the movement of data and computation between edge, local HPC, and cloud resources.

Key methods: Edge-to-cloud workflow orchestration, data assimilation, IoT integration, hybrid HPC/cloud architectures.

Digital Twinning of High-Value Infrastructure

A digital twin is a persistent, physics-informed computational model of a physical system — one that stays current as the system evolves or as new data arrives. ACIC develops digital twin frameworks for marine infrastructure, ports, and other high-value assets, combining the group's strengths in fluid simulation, HPC, and data integration.

Key methods: Digital twin architecture, physics-based model updating, sensor fusion, visualization.