Scheduling methods for modular shipbuilding

In the field of shipbuilding, there is a growing demand for faster and more efficient production processes, along with a need for swift adoption of new technologies. Modular production emerges as a potential solution, involving the development of a product family with a base platform and various modules. Instead of designing and producing each...

Optimal Ship Fuel Selection under Life Cycle Uncertainty

Shipowners need to prepare for low-emission fuel alternatives to meet the IMO 2050 goals. This is a complex problem due to conflicting objectives and a high degree of uncertainty. To help navigate this problem, this paper investigates how methods that take uncertainty into account, like robust optimization and stochastic optimization, could be...

Linear Time-Varying Parameter Estimation: Maximum A Posteriori Approach via Semidefinite Programming

We study the problem of identifying a linear time-varying output map from measurements and linear time-varying system states, which are perturbed with Gaussian observation noise and process uncertainty, respectively. Employing a stochastic model as prior knowledge for the parameters of the unknown output map, we reconstruct their estimates...

Global Techno-Economic Feasibility of Far Offshore Green Hydrogen Production towards 2050

With space constraints onshore, strong renewable resources available far offshore<br/>and growing green hydrogen demand, far offshore green hydrogen production<br/>may be an attractive option. To assess this potential, a literature review was<br/>conducted to identify the relevant technologies to be considered and suitable<br/>modelling methods....

3D Shape Optimization of Consecutive Manifolds using Free Form Deformation and Adjoint-Based Methods

Current design methods for oblique manifolds were first presented in the paper of London et al. in 1968. This method presents a single equation to shape the dividing manifold of several manifold configurations. However, current literature shows a potential to improve the current design method by implementing advanced techniques. This paper aims...

Optimizing the pump schedule of water distribution systems using a deep learning meta-model: To what extent can algorithm unrolling optimize the pump schedule of an urban water distribution system?

This thesis investigates the integration of algorithm unrolling and genetic algorithms (GA) for optimizing pump scheduling in water distribution systems (WDS), a critical component for ensuring energy-efficient water delivery. In the context of modern civilization’s reliance on clean, affordable water for diverse uses, the operation of a WDS,...

Optimization of Acoustic Metasurfaces with Hybrid Structures for attenuation of broadband low frequency sound: An exploratory research on hybrid metamaterials to analyze/uncover possible practical applications/benefits for sound attenuation

We perform a study on acoustic metasurfaces, aiming to achieve simultaneously low resonance frequencies (below 400 Hz), high attenuation bandwidth (greater than 200 Hz), and high attenuation coefficient magnitudes (above 0.8), while maintaining a surface-like structure.<br/>We propose the implementation of geometrical optimization through...

Design and Optimization of Hyperboloid Lattice Structures for Timber Towers: A Study on Stiffness and Material Efficiency

The presented research aims to design and optimize a timber observation tower, with a primary focus being the influence of topological and curvature parameters on its stability and lateral stiffness in resistance to non-uniform wind load profiles. <br/><br/>Having recognised the environmental benefits and urgency to find other alternatives,...

Minimize experimentation overhead through dataset selection, ensemble feature attention, and feature selection with reduced subset sizes

In large-scale ML, data size becomes a critical variable, especially in the context of large companies, where models already exist and are hard to change and fine-tune. Time to market and model quality are essential metrics, thus looking for ways to select, prune and augment the input data while treating the model as a black box can speed up the...