Sponsored Projects

The goal of this proposed project is to develop and test a scaled prototype of Surface Riding Wave Energy Converter (SR-WEC) that can result in a market-disruptive Levelized Cost of Energy (LCOE) by combination of 1)extended operating window, 2) substantially lowered costs, and 3) amplified average power output by simple optimum control. Objectives to attain the goal are 1) to complete optimum design of SR-WEC for the maritime market applications, 2) to confirm full performance of the SR-WEC using scalable wave tests of the scaled prototype in the ocean basin and advanced global performance simulation, 3) to confirm the market disruptive LCOE less than 40 cents/kWh for single operation in the target application using the global performance simulation correlated with the scalable tests, and 4) identify remaining uncertainties and risks to be resolved in the larger scale prototype tests. For the standards and certificates, IEC TS 62600-2 and American Bureau of Shipping (ABS) Guidance on Approval of Novel Concepts are considered. Prototype dimension in the full scale will be optimized out of outer diameter from 1 to 5 m and total cylinder length from 5 to 20 m. Target scale of the wave tests will be 1/15 to 1/20 scale.

This project 1) completes the optimum design of GPE Ocean Blanket with a scalable detail design, which will improve the performance of wave energy conversion through adaptive resonance, 2) proves the concept by fabrication and test of a pre-prototype at a smaller scale using a actuators-based testbed and 2D wave basin, and 3) proves the designed performance of wave energy conversion by fabrication and test of a prototype at a scalable representative scale using field test at the Galveston offshore.  

We 1) develop an innovative method of building instantaneous “dynamics model” from onboard measurements, 2) combine it with real-time optimum controls as the Adaptive Optimum Control, and 3) deploy at Oceaneering Freedoms for the adaptable optimum operations with known-unknowns and unknown-unknowns.

Develop the Digital Twin Framework of a floating platform system in offshore oil and gas applications, which achieve real-time monitoring of structural integrity from the on-board measurement at existing sensors. The efficacy of the developed Digital Twin Framework is examined through applying numerical data simulated by the coupled hydroelastic analysis.

The goal of this project is to identify the critical factors and the criteria of transition between manual and autonomous modes of operation for marine vessels. Critical factors including safety, reliability, robustness, performance, and risk and consequence of failure will be investigated.  The focus in the first year of the project will be on autonomous functions associated with autonomous navigation of marine vessels with an emphasis on facilitating human operators to remotely control and monitor multiple vessels from a ship or a shore based station. 

We will develop a model-based simulation framework for Autonomous Navigation with Collision Detection and Collision Avoidance (CDCA). This framework will develop and incorporate high fidelity dynamic models for the marine vessel, sensors and the neighboring ships/vessels as well as the control algorithms for autonomous navigation of the marine vessel. The developed framework will be employed to conduct verification and validation of the specifications in the autonomous mode of the autonomous navigation function for various marine navigation scenarios.

This project will enhance the accuracy and robustness of the key components and their integration for autonomous CDCA by: (1) incorporating high-fidelity dynamic models, sensors and control algorithms for marine vessels equipped with various sensing platforms, (2) conducting verification and validation of the specifications for autonomous navigation functions across a wide variety of navigation scenarios, and (3) collaborating with ABS to identify autonomy vendors and engage and consult with them. The primary goal is to advance the virtual simulation framework to support ABS’s certification process.