A.A. Kana
Please Note
77 records found
1
Multi-fidelity design framework to support early-stage design exploration of the AXE frigates
The vertical bending moment case
Early-stage design assessment of loads such as vertical bending moments can be a critical quantity of interest for design exploration. Traditionally, classification societies’ rules are used to calculate such loads. However, relying solely on these rules for designing new vessels may be insufficient, and conducting direct analyses of a large number of designs to support design exploration is computationally infeasible. Currently, key factors such as wave-induced loads are typically evaluated only in later design stages, where a limited number of promising designs are under consideration. This research explores the potential of harnessing multi-fidelity models for early-stage predictions of wave-induced loads, with a specific focus on wave-induced vertical bending moments. As an initial step in this direction, the vertical bending moment analysis was simplified to consider responses in a regular sea state, where the wavelength matches the vessel’s length. The assessed multi-fidelity models include the application of both linear and nonlinear Gaussian processes and compositional kernels to improve predictions of wave-induced loads, specifically focusing on wave-induced vertical bending moments. The case study focuses on the early-stage exploration of the AXE frigates. Multi-fidelity models were constructed using both frequency- and time-domain methods to evaluate the vertical bending moments experienced by the hull. Finally, a critical reflection is provided on how traditional early-stage design processes can be enhanced by integrating multi-fidelity models.
Alternative fuels are essential to decarbonising maritime transport, provided they retain high energy and power density; hydrogen carriers fulfil these criteria and represent a promising fuel option. This research quantifies the power-energy trade-offs of four hydrogen carrier fuels: namely, sodium borohydride, ammonia borane, n-ethylcarbazole, and dibenzyltoluene. Each hydrogen carrier is combined with four energy converters: proton exchange membrane fuel cell (PEMFC), internal combustion engine (ICE), solid oxide fuel cell (SOFC), and gas turbine, respectively, resulting in 16 outcomes, which were assessed using Ragone plots. For each hydrogen carrier, one energy converter is selected as a case study. Four reference cases are also examined: marine diesel oil (MDO) and methanol combined with ICE, ammonia with SOFC, and liquid hydrogen with PEMFC. These 8 case studies (carrier and converter combinations) are evaluated for performance across several shipping applications. The results indicate that ammonia borane combined with ICE and sodium borohydride combined with a PEMFC offer energy and power density profiles suitable for various vessel types, including inland ships and ocean-going vessels. These combinations also show potential for specialised vessels such as fishing boats, dredgers, tugs, and ferries, which operate under unique load profiles and duty cycles. Compared with alternative fuels, such as ammonia, methanol, and liquid hydrogen, hydrogen carriers can demonstrate higher energy and power densities. Under specific circumstances, they may achieve performance comparable to MDO, highlighting their potential for zero-emission maritime propulsion.
This paper presents a design space exploration (DSE) for the development of an innovative special-purpose installation vessel for tension leg platform (TLP) floating offshore wind turbines. The concept, named “Windchanger,” features an installation deck integrated with the stern design to facilitate turbine lowering and recovery. The DSE model conducts a tradeoff analysis using a parametric model of the hull and installation deck, evaluating both technical feasibility and cost-effectiveness. The model evaluates various scenarios across two demonstration operational areas: the North Sea and the U.S. East Coast. Results evaluated the principle design limitation across various TLP designs, ship concepts, installation design concepts, and operational scenarios. Findings indicate that the transport capacity measured in the number of TLPs, from 1 to 5, has a significant influence on design considerations and economic effectiveness. The overall results show that the Windchanger concept has the potential to be a competitive installation solution.
– Hydrogen carriers, such as liquid organic hydrogen carriers (LOHCs) and borohydrides, are promising zero-emission alternative fuels for ships. Bringing these hydrogen carriers on board, however, creates new challenges. A major challenge is their spill behaviour. Knowing the spill behaviour is paramount to avoid large-scale environmental disasters. This paper investigates the spill behaviour of four hydrogen carriers (and their conjugates): sodium borohydride, ammonia borane, dibenzyltoluene, and n-ethylcarbazole. The hydrogen carriers were all dissolved in artificial seawater to test their behaviour. Sodium borohydride reacts with seawater, as it also reacts with pure water. However, contrary to expectations, it reacts faster with seawater than regular water. The reaction mechanism behind this is unknown. Ammonia borane does not visibly react with normal water or with seawater. Dibenzyltoluene sinks and forms tiny bubbles which are easily perturbed. Unfortunately, perhydro dibenzyltoluene could not be tested due to technical problems. N-ethylcarbazole breaks up into smaller pieces and predominantly stays afloat, likely due to the surface tension of water. Perhydro n-ethylcarbazole floats but is barely visible in seawater due to its transparency. Preventive measures must be established to avoid large-scale spills if these substances are utilised on ships, as they are likely challenging to clean up.
Design space reduction decisions made in set-based design use perceptions of feasibility to eliminate unfavorable design solutions from consideration. Perceptions are formed with incomplete information, leaving them susceptible to change if new and conflicting information is made available later in the design process. This paper considers how new information originating from newly sampled design points can alter perceptions of feasibility and introduces a probabilistic and an entropic strategy for quantifying the risk of prematurely eliminating potential design solutions. Emergent designs of automated set-based design simulations gauging this risk are evaluated against ones neglecting it for an analogous design problem. The Python-based simulations have different disciplines randomly explore their design spaces and generate reasonable space reduction propositions, and then they give a design manager the opportunity to check the fragility of reduced design spaces before finalizing any reductions. Gathered results indicate that both the probabilistic and entropic models are able to effectively delay design decisions and help disciplines maintain a higher diversity of design solutions while designer understanding is still growing. Both models effectively delay risky space reductions and encourage a more gradual reduction of design spaces compared to simulations not including fragility checks. Furthermore, as the entropic model takes a more holistic approach by working with the history of perceptions formed in a discipline's design space rather than just the newest perceptions, space remaining and diversity results show it slightly outperforming the probabilistic model.
Quantum Neural Networks
A Path to Lower Emissions Through Fuel Consumption Prediction in Shipping
This paper proposes Quantum Neural Networks (QNNs) as a data-driven approach for predicting fuel consumption. We utilize various layer architecture designs available in the Torchquantum framework, including both entangled and non-entangled circuit designs. In general, QNNs can achieve comparable Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) with significantly fewer trainable parameters. Neither pure QNNs nor hybrid QNN models exhibit the underfitting tendencies seen in classical neural networks (CNNs). Notably, one of the most significant findings of this work is that hybridizing or”dressing” the quantum circuit leads to substantial improvements in RMSE and MAPE for pure QNNs. These promising results suggest potential optimizations for reducing emissions in green shipping.
thus the shape of the generated design space. ...
thus the shape of the generated design space.
Hydrogen carriers are attractive alternative fuels for the shipping sector. They are zero-emission, have high energy densities, and are safe, available, and easy to handle. Sodium borohydride, potassium borohydride, dibenzyltoluene, n-ethylcarbazole, and ammoniaborane are hydrogen carriers with high theoretical energy densities. The energy density is paramount to implementing hydrogen carriers as a high energy density enables compact and lightweight storage. The effective energy density depends on integrating heat and masses with energy converters. This combination defines the energy efficiency and, thus, the energy density of the system. This paper addresses the effective energy density of the hydrogen carriers, including the dehydrogenation process. Using a 0D model, we combined the five carriers with two types of fuel cells, namely proton exchange membrane (PEM) and solid oxide fuel cells (SOFC), an internal combustion engine and a gas turbine. N-ethylcarbazole and dibenzyltoluene offer medium energy densities, reaching almost 4 MJ/kg. However, the effective energy density of sodium borohydride and ammoniaborane is very high, up to 15 MJ/kg, including the energy converter. This is similar to the energy density of marine diesel oil combined with an internal combustion engine. Thus, we conclude hydrogen carriers are alternative fuels that deserve more attention because of their strong potential to make shipping zero-emission.
on the effect of EC on the actual engine room layout. The state-of-the-art literature has typically addressed these two challenges separately. This study proposes a design method to bridge these two fields by combining the use of (1) Markov decision processes to assess uncertain future methanol EC developments during the vessel lifecycle and (2) a generative probabilistic layout algorithm to quantify the risks associated with the EC systems layout integration. The case study identifies the drivers behind the EC technology choice during the lifecycle of a notional yacht vessel. ...
on the effect of EC on the actual engine room layout. The state-of-the-art literature has typically addressed these two challenges separately. This study proposes a design method to bridge these two fields by combining the use of (1) Markov decision processes to assess uncertain future methanol EC developments during the vessel lifecycle and (2) a generative probabilistic layout algorithm to quantify the risks associated with the EC systems layout integration. The case study identifies the drivers behind the EC technology choice during the lifecycle of a notional yacht vessel.
Retrofit modeling for green ships
A data-driven design approach for emission reduction using bunker delivery notes
Ship Design in the Era of Digital Transition
A State-of-the-Art Report