Preliminary Bulbous Bow Design Tool Applying K Nearest Neighbours Classification and Regression Model

Designing bulbous bows for ships remains a challenging task. Their impact on different design attributes as well as their change in performance when operating off their intended design condition renders this as a multidimensional problem. This paper explores the application of machine learning techniques to a sample of in-service vessel data to develop a preliminary design tool. The ships' data was analysed together with their bulbous bow data to generate machine learning models using a supervised approach. The K Nearest Neighbours Classifier and Regression models were used as the basis of the tool. Together, these models can be used to predict whether to install a bulbous bow and the recommended dimensionless coefficients for new vessels. Generating this preliminary bulbous bow design tool required the introduction of new dimensionless coefficients that discretise the bulbous bow's longitudinal section. The preliminary design tool gives the designer the ability to determine whether a bulbous bow should be fitted and, if so, to obtain an initial estimate of the bulbous bow required for the vessel being designed, based on key input parameters that relate to the ship and its operation. The new design tool is demonstrated to provide preliminary design details for bulbous bows through the case studies.

Enabling quality of urban spaces in Cairo’s new suburban settlements: a community character approach for New Cairo, Egypt

A global concern claims that activities and functions that once filled traditional public spaces are privatized being less and less oriented to the public. In Cairo’s new settlements, public spaces don’t seem to contribute to its public life. Each community’s most valuable assets are the ones they already have; thus, urbanisms advocate the role of retaining traditional street patterns, vistas, and landscape of a community’s distinct character. The research aim is to identify design attributes to be added to the literature in terms of designing public spaces for the specific cultural context of Cairo, Egypt, and its new suburban settlements. The methodology then follows a comparative analysis study to reach the desired objectives of buildings a community character approach. In an exploratory method, two case studies of public spaces in Cairo are chosen following a purposive selection most relevant to the study. The target is to choose two cases in proximity for users to be familiar with the two of them and enable a reliable comparison. It then conducts a survey that involves the user’s evaluation of their public spaces in correlation to their needs. Jan Gehl’s twelve criteria are adopted by this paper’s field investigation for the assessment of public spaces’ quality. Findings of the study include an elaboration on Jan Gehl’s twelve criteria either by highlighting the importance of existing aspects or the addition of further criteria that showed value to public space quality and their users. The findings provide guidelines that help in designing quality public spaces in Cairo’s new settlements. The added value from this study is in identifying a set of factors or attributes that consider users’ needs for a given cultural context.

The Future of Forecasting Competitions: Design Attributes and Principles

Forecasting competitions are the equivalent of laboratory experimentation widely used in physical and life sciences. They provide useful, objective information to improve the theory and practice of forecasting, advancing the field, expanding its usage, and enhancing its value to decision and policymakers. We describe 10 design attributes to be considered when organizing forecasting competitions, taking into account trade-offs between optimal choices and practical concerns, such as costs, as well as the time and effort required to participate in them. Consequently, we map all major past competitions in respect to their design attributes, identifying similarities and differences between them, as well as design gaps, and making suggestions about the principles to be included in future competitions, putting a particular emphasis on learning as much as possible from their implementation in order to help improve forecasting accuracy and uncertainty. We discuss that the task of forecasting often presents a multitude of challenges that can be difficult to capture in a single forecasting contest. To assess the caliber of a forecaster, we, therefore, propose that organizers of future competitions consider a multicontest approach. We suggest the idea of a forecasting-“athlon” in which different challenges of varying characteristics take place.

A MODIFIED ANALYTICAL HIERARCHY PROCESS DESIGN EVALUATION METHODS FOR PRODUCT RECOVERY

The absence of existing standards for product recovery planning and the associated difficulty in prioritising the conflicting design requirements are among the main challenges faced during product design. In this paper, a concept for the Design for Multiple Life-Cycles (DFMLC) is proposed to address this situation. The objective of the DFMLC model is to assist designers in evaluating design attributes of Multiple Life-Cycle Products (MLCP) at the early design stage. The methodology adopted for the evaluation of MLCP design strategies has been based on a modified Analytical Hierarchy Process (AHP). Two mapping matrices of the design guidelines and design strategies concerning MLCP design attributes were developed for the modified AHP model. Disassemblability (> 21 %) was found to be the most important design element for MLCP followed by serviceability (> 20 %) and reassembly (> 12 %).