The present work discusses an innovative approach to metamodeling in reliability that uses a field-transversal rationale. Adaptive metamodeling in reliability is characterized by its large spectra of models and techniques with different assumptions. As a result, the reliability engineer is frequently faced with the highly challenging task of selecting an appropriate model or technique with limited a priori knowledge about the performance function that defines the problem of reliability. To tackle this challenge, a complement-basis is proposed for adaptive metamodeling. It consists in using a batch of multiple metamodels or techniques that, accordingly to an activation criterion, are selected to solve the reliability analysis. This activation is set to depend on the model synergy with the problem in-hand. In the present work the leave-one-out loss is applied as evaluator of compatibility, and results show that the absolute loss successfully performs as an activator. A metamodel-independent learning approach and stopping criterion are implemented to study the proposed approach in five representative examples. Results show that the complement-basis allows to increase the efficiency of the reliability analysis through the selection of adequate metamodels, which is indicative of the untapped potential that further transversal research may add to metamodeling in reliability analysis.

The first Irish public Bike Sharing Scheme (BSS) was launched in Dublin in 2009. Dublinbikes has been internationally recognised as one of the most successful bike-sharing rental schemes in the world. For this reason, among others, the cities of Cork, Limerick and Galway launched their own BSSs at the end of 2014. The objective of this paper is to compare the performance of the four BSSs during the first two years of implementation in each Irish city according to endogenous factors, such as the physical design of the schemes, and exogenous factors, such as city size and population density. In terms of population, Limerick and Galway are small cities, Cork is a medium-sized city and Dublin is a large city. In consequence, the results cover the main relevant aspects of BSSs according to the size of the scheme, pointing out similarities and differences among BSS of different sizes. The main findings indicate that the number of daily rentals per bike is a good metric from the point of view of the transport operator. However, a higher density of bikes, stations and docking points does not imply greater usage, whereas the size of the deployment area could be a key factor in improving bike usage. Finally, a synopsis of the essential aspects to consider when designing a BSS deployment based on types of users in small cities is provided.

Construction Management and Engineering students need to acquire managing skills for solving real-world problems that are complex, rarely straightforward and lack 'one right answer'. For this, they need to become 'open designers', capable to be reflective, integrative and creative in- and on action with dynamic and new situations. In this paper, the so-called Open Design Learning Circle (ODLC) will be proposed as an innovative educational concept in which engineering-, management- and pedagogic sciences are integrated. Within this concept the students 'dialogue' with: 1) an objective open glass box model covering engineering products and management processes (outer) and, 2) their subjective open human threefold, reflecting their personal learning (inner). The integration of both human and model dialogues is essential for the emergence of new knowledge and creative insights for open designs, which is essentially distinct from more traditional learning concepts. To enable this emergence, a self-chosen system of interest is the 'experiential vehicle' that forms the basis for a self-created textbook and model. Thereby, the ODLC forms the fundamental basis for creating 'open and persistent learners'. In this paper, it also will be shown how the ODLC can be operationalized into a learning cycle and how it has been implemented in an example course on systems engineering management within the MSc Construction Management Engineering curriculum at the TU Delft. Finally, some preliminary student findings and next steps for further research are discussed.

Estimating reliable projections of precipitation considering climate change scenarios is important for hydrological studies. General circulation models provide future climate simulations at large scale in terms of large-scale atmospheric variables (LSAVs). Those LSAVs can be downscaled to finer special resolution using several downscaling approaches. This paper presents a support vector regression (SVR)-based downscaling approach to downscale rainfall at several locations in a study area. Because the rainfall generation mechanisms cannot be the same for all the sites in a study area, conventional multisite downscaling approaches that assume the same rainfall generation mechanism should not be used. Therefore, a new downscaling approach is proposed that (1) divides the study area in several climatological regions, and (2) develops different downscaling models for each of the climatological regions to obtain future projections of rainfall. The new approach was implemented on rainfall data obtained for Republic of Ireland to demonstrate the effectiveness of the approach compared with existing approaches. Future projections of rainfall were obtained for the period 2012-2050 corresponding to four Representative Concentration Pathway climate change scenarios. The performance of the SVR approach was compared with that of relevance vector machine-and deep learning-based downscaling approaches.

Simulation-based education (SE) refers to the use of simulation software, tools, and serious games to enrich the teaching and learning processes. Advances in both computer hardware and software allow for employing innovative methodologies that make use of SE tools to enhance the learning experience. Moreover, thanks to the globalisation of e-learning practices, these educational experiences can be made available to students from different geographical regions and universities, which promotes the development of international and inter-university cooperation in education. This paper provides a review of recent works in the SE subject, with a focus on the areas of engineering, science, and management. It also discusses some experiences in SE involving different European universities and learning models. Finally, it also points out open challenges as well as noticeable trends.

Reliability assessment with adaptive Kriging has gained notoriety due to the Kriging capability of accurately replacing the performance function while performing as a self-improving function for learning procedures. Recent works on adaptive Kriging pursued to improve the efficiency of the active learning through the application of distinct learning functions, sampling methods, or frameworks to assess the learning space. Within this context, the present work exploits three innovative applications of density scanning to improve the efficiency of the adaptive Kriging. Density scanning has significant synergies with adaptive Kriging implementation. For most learning criteria, candidate points occur in dense clusters. This is due to the fact that the most efficient learning strategies pursue to improve predictions near the failure region, or when the prediction uncertainty is large. Identifying dense clusters of points, and fomenting exploitation of these, parallelizing computations, and limiting the generation of dense clusters in the design of experiments are examples of learning frameworks that can be achieved with density scanning. Three reference examples are researched in the present work, a complex function, a series system, and a relatively high dimension engineering problem. For all the cases, the application of density scanning is identified to improve the active learning efficiency.

When analysing the performance of bike-sharing scheme (BSS) stations, it is common to find stations that are located in specific points that capture the interest of users, whereas nearby stations are clearly underused. This uneven behaviour is not totally understood. This paper discusses the potential factors influencing station attractiveness, supported by the related literature on cyclists’ and pedestrians’ preferences and the characteristics of the stations themselves. The existing literature addresses these topics independently, while this work unites them by proposing a non data-extensive methodology that allows the attractiveness of BSS stations to be assessed. Attractiveness in this context is understood as the set of physical, environmental and service-related features of a bike station that make it more appealing for BSS users than nearby stations. Special attention is paid to differentiating objective features, based on facts, from subjective features, those influenced by personal perceptions. This classification becomes important in this context because subjective aspects can change from one geographical location to another, making the findings related to these aspects difficult to apply to other regions. Moreover, the assessment of the stations’ levels of safety and security is included. Thus, the proposed measure of attractiveness of BSS stations provides a balanced overview of several features. The consideration of station attractiveness when designing BSS layouts will help to refine the design of new layouts and will assist in conducting an appropriate diagnostic evaluation of the existing ones. This tool will allow urban and transportation planners to reduce re-balancing costs and to maximise user satisfaction at a low cost, which have a direct impact on improving the urban sustainability. The proposed method is applied to the Dublin bike sharing scheme, Dublinbikes, with good performance results.

The characteristics of civil structures inevitably suffer a certain level of damage during its lifetime and cheap, non-destructive and reliable methods to assess their correct performance are of high importance. Structural System Identification (SSI) using measured response is the way to fine why performance is not correct and identify where the problems can be found. Different methods of SSI exist, both using static and vibration experimental data. However, using these methods is not always possible to decide if available measurements are sufficient to uniquely obtain the unknown. A (SSI) method that uses constrained observability method (COM) has already been developed based on the information provided by the monitoring of static non-destructive tests - using deflections and rotations under a known loading case. The method assures that all observable variables can be obtained with the available measured data. In the present paper, the problem of determining the actual characteristics of the members of a structure such as axial stiffness, flexural stiffness and mass using vibration data is analyzed. Subsets of natural frequencies and/or modal shapes are used. To give a better understanding of the proposed method and to demonstrate its potential applicability, several examples of growing complexity are analyzed, and the results show how constrained observability techniques might be efficiently used for the dynamic identification of structural systems using dynamic data. These lead to significant conclusions regarding the functioning of an SSI method based on dynamic behavior.