This thesis investigates the implementation of modularity in the early-stage design process of custom luxury yachts, specifically targeting the Feadship fleet between 75 and 110 meters. The research aims to determine whether modular design methods can optimize efficiency and creativity while maintaining the high degree of customization demanded by clients. To address this, the thesis introduces Modular Function Deployment (MFD) as a structured framework for identifying and evaluating yacht systems suitable for modularization.

Key insights from the study demonstrate that MFD, coupled with innovative tools such as the Area Prediction tool and the Arrangement Generator tool, can enhance both design creativity and efficiency. Contrary to concerns that modularity might restrict creativity, these tools offer designers a structured yet flexible platform for exploring numerous configurations. This encourages the exploration of innovative design arrangements that push the boundaries of conventional yacht architecture.

The study also focuses on evaluating how designers can benefit from modular principles. The Area Prediction tool, based on the Random Forest regression model, predicts the surface areas of different yacht modules. The Arrangement Generator tool allows designers to visualize potential layouts, iterating through various combinations rapidly. These tools support designers in generating new, optimized arrangements that maintain high levels of customization. A case study with Feadship designers highlights the fact that modularity offers substantial benefits, although challenges remain in terms of integrating these tools fully into the creative process.

Future research is suggested to explore whether yacht clients will accept modularity without perceiving the designs as less bespoke, how designers can shift from traditional bespoke methods to modular approaches, and how regulatory challenges may be navigated. But more important, the impact of the ongoing energy transition on future yacht designs is considered significant, necessitating future updates to the prediction tools as yacht specifications evolve.

Background: Pharmacokinetic (PK) models can describe microvascular density and integrity. An essential component of PK models is the arterial input function (AIF) representing the time-dependent concentration of contrast agent (CA) in the blood plasma supplied to a tissue. Purpose/Hypothesis: To evaluate a novel method for subject-specific AIF estimation that takes inflow effects into account. Study Type: Retrospective study. Subjects: Thirteen clinical patients referred for spine-related complaints; 21 patients from a study into luminal Crohn's disease with known Crohn's Disease Endoscopic Index of Severity (CDEIS). Field Strength/Sequence: Dynamic fast spoiled gradient echo (FSPGR) at 3T. Assessment: A population-averaged AIF, AIFs derived from distally placed regions of interest (ROIs), and the new AIF method were applied. Tofts' PK model parameters (including v_p and K^trans) obtained with the three AIFs were compared. In the Crohn's patients K^trans was correlated to CDEIS. Statistical Tests: The median values of the PK model parameters from the three methods were compared using a Mann–Whitney U-test. The associated variances were statistically assessed by the Brown-Forsythe test. Spearman's rank correlation coefficient was computed to test the correlation of K^trans to CDEIS. Results: The median v_p was significantly larger when using the distal ROI approach, compared to the two other methods (P < 0.05 for both comparisons, in both applications). Also, the variances in v_p were significantly larger with the ROI approach (P < 0.05 for all comparisons). In the Crohn's disease study, the estimated K^trans parameter correlated better with the CDEIS (r = 0.733, P < 0.001) when the proposed AIF was used, compared to AIFs from the distal ROI method (r = 0.429, P = 0.067) or the population-averaged AIF (r = 0.567, P = 0.011). Data Conclusion: The proposed method yielded realistic PK model parameters and improved the correlation of the K^trans parameter with CDEIS, compared to existing approaches. Level of Evidence: 3. Technical Efficacy Stage 1. J. Magn. Reson. Imaging 2018;47:1197–1204.