Operability assessment of multibody offshore operations is commonly performed using large numbers of high-fidelity time-domain simulations. When environmental conditions are discretised across realistic ranges of wave, wind, and current parameters, simulation campaigns can involve up to 10⁵ individual three-hour runs, resulting in substantial computational cost. This challenge is shared across a broad class of coupled floating-body operations, including offshore hydrocarbon offloading, CO₂ ship-to-ship transfer, and floating wind installation.

This thesis investigates the use of data-driven prediction models to support simulation-driven operability assessment while retaining response-based decision criteria, using an FLNG–LNGC side-by-side offloading configuration as a case study. The study is based on a simulation dataset produced by the Maritime Research Institute Netherlands (MARIN) for Shell, consisting of time-domain simulations of a spread-moored FLNG with an LNG carrier in side-by-side configuration. From this dataset, a sea-wave subset of 8317 simulations is used for model development and evaluation. Each simulation includes summary response extrema as well as full time-series records of wave elevation, vessel motions, mooring line tensions, and fender loads.

Two complementary machine learning (ML) approaches are considered. The first is a summary-statistics-based learning (SSBL) approach, which predicts operability-limiting response extrema directly from static environmental descriptors using feed-forward regression models. The second is a time-series-based learning (TSBL) approach operating on full response time series. Within this framework, a segment-based forecasting model based on long short-term memory (LSTM) networks and a full time-series model based on transformer architectures with cross-attention heads are employed. For time-series modelling, response signals are decomposed into wave-frequency and low-frequency components to distinguish first-order wave-induced behaviour from second-order drift-dominated dynamics.

At a training fraction of approximately 70%, wave-frequency models achieve mean coefficients of determination R² between 0.6 and 0.8, while low-frequency LSTM models attain mean R² values of approximately 0.8. To reduce training requirements while preserving operability-critical behaviour, a compact training dataset of 1500 simulations is derived using a two-stage selection strategy combining stratified sampling over key sea-state parameters with K-means clustering in response space.

For operability classification based on response extrema across the full sea-wave dataset, a multilayer perceptron trained on the reduced dataset achieves an overall accuracy of 98.22% for 6816 unseen sea states. Time-series-based models achieve an overall classification accuracy of 86.7% and enable reconstruction of complete multibody response histories when the training data sufficiently represent dominant physical regimes, including head-sea, beam, and near-beam wave conditions.

From a computational perspective, the original MARIN sea-only time-domain simulations require approximately 1428 core-hours to evaluate 8317 sea states. In contrast, transformer-based time-series models require approximately 18.9 GPU-hours for one-time training on 1500 sea states and 2.85 GPU-hours for prediction over the remaining sea states, while extrema-based model prediction is effectively instantaneous. These results demonstrate that data-driven models can substantially reduce the computational burden of simulation-driven operability assessment for coupled floating-body systems more broadly. ... Read more

The Nahuel Huapi National Park, in the Lake District of Northern Patagonia, Argentina, is well known for its tourism industry all year round. After COVID-19, the area saw a significant increase in the number of tourists traveling to the area. This means that the lake located in the heart of the district, Lago Nahuel Huapi, is being used more and more to explore the environmental richness of the area by boat. Now, the capacity of mooring spaces is no longer sufficient in the region, resulting in the construction of illegal private docks along the shore. To reduce this impact on the environment the authorities granted in 2024 a concession to develop one of the last not yet commercialized marina’s in the region: the marina in Bahía López.

This report provides a consult for the concessionaire of this development. The process begins with a research phase, consisting of an area study, and the mapping of environmental and hydrodynamic constraints. Subsequently, stakeholders are categorized, as the development of a marina in a national park entails complex regulations from multiple organizations. The outcomes of the research phase are translated into specific functional requirements for the marina. These functional requirements are the basis for the next phase, the design phase. This phase begins with the formulation of a design vision statement, formulating the project response to local conditions. Based on this, three different conceptual designs with various technical solutions are developed. Through a multi-criteria analysis, the concepts are tested on their robustness in order to chose a final concept. This concept is then elaborated into a preliminary design. Presenting an overview of the marina’s facilities, including structural designs, operational needs, and capital costs. Finally, suggestions for future development
are provided, outlining the next steps to advance the marina to a next phase.
... Read more