Optimization of multicore optical fibers with fiber Bragg gratings towards bend and shape sensing

A shape sensor based on fiber Bragg gratings (FBGs) in multicore fibers is a complex device with multiple factors which have to be accounted for a successful measure- ment system. In this dissertation, I considered several aspects of such shape and curvature sensors

Characterization and Modelling of Composites

Composites have increasingly been used in various structural components in the aerospace, marine, automotive, and wind energy sectors. The material characterization of composites is a vital part of the product development and production process. Physical, mechanical, and chemical characterization helps developers to further their understanding of products and materials, thus ensuring quality control. Achieving an in-depth understanding and consequent improvement of the general performance of these materials, however, still requires complex material modeling and simulation tools, which are often multiscale and encompass multiphysics. This Special Issue aims to solicit papers concerning promising, recent developments in composite modeling, simulation, and characterization, in both design and manufacturing areas, including experimental as well as industrial-scale case studies. All submitted manuscripts will undergo a rigorous review process and will only be considered for publication if they meet journal standards. Selected top articles may have their processing charges waived at the recommendation of reviewers and the Guest Editor

Scour detection with monitoring methods and machine learning algorithms - a critical review

Foundation scour is a widespread reason for the collapse of bridges worldwide. However, assessing bridges is a complex task, which requires a comprehensive understanding of the phenomenon. This literature review first presents recent scour detection techniques and approaches. Direct and indirect monitoring and machine learning algorithm-based studies are investigated in detail in the following sections. The approaches, models, characteristics of data, and other input properties are outlined. The outcomes are given with their advantages and limitations. Finally, assessments are provided at the synthesis of the research.This research was funded by FCT (Portuguese national funding agency for science, research, and technology)/MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE), under reference UIDB/04029/2020 and trough the doctoral Grant 2021.06162.BD. This work has also been partly financed within the European Horizon 2020 Joint Technology Initiative Shift2Rail through contract no. 101012456 (IN2TRACK3)

The Public Service Media and Public Service Internet Manifesto

This book presents the collectively authored Public Service Media and Public Service Internet Manifesto and accompanying materials.The Internet and the media landscape are broken. The dominant commercial Internet platforms endanger democracy. They have created a communications landscape overwhelmed by surveillance, advertising, fake news, hate speech, conspiracy theories, and algorithmic politics. Commercial Internet platforms have harmed citizens, users, everyday life, and society. Democracy and digital democracy require Public Service Media. A democracy-enhancing Internet requires Public Service Media becoming Public Service Internet platforms – an Internet of the public, by the public, and for the public; an Internet that advances instead of threatens democracy and the public sphere. The Public Service Internet is based on Internet platforms operated by a variety of Public Service Media, taking the public service remit into the digital age. The Public Service Internet provides opportunities for public debate, participation, and the advancement of social cohesion. Accompanying the Manifesto are materials that informed its creation: Christian Fuchs’ report of the results of the Public Service Media/Internet Survey, the written version of Graham Murdock’s online talk on public service media today, and a summary of an ecomitee.com discussion of the Manifesto’s foundations

Application of surrogate modeling methods in simulation-based reliability and performance assessment of civil structures

Structures and infrastructure systems are subjected to various deterioration processes due to environmental or mechanical stressors. Proper performance assessment approaches capable of detecting potential structural damage and quantifying the probability associated with structural failure are required to formulate optimal maintenance and retrofit plans that minimize the risk of failure and maximize the safety of structures. However, due to the presence of several sources of uncertainty that can affect the performance assessment and decision-making processes (e.g., uncertainties associated with loading conditions and performance prediction models), applying probabilistic methods, such as Monte Carlo simulation, is essential. In this context, a large number of simulations is generally required to quantify the low failure probability associated with civil structures. Executing the required number of simulations may be computationally expensive, especially if complex and/or nonlinear structural models (e.g., finite element models) are involved. The use of surrogate modeling tools such as artificial neural networks, polynomial chaos expansion, and kriging can help in reducing the computational costs associated with simulation-based probabilistic analysis. The research proposed herein aims to develop probabilistic approaches for performance assessment and damage detection of structures using advanced simulation-based techniques coupled with surrogate modeling. The proposed methodology is applied to quantify the risk of bridge failure due to flood events considering the impact of climate change. The approach was extended to establish the time-variant flood fragility surfaces for bridges under flood conditions. This approach (a) integrates deep learning neural networks into a simulation-based probabilistic approach to predict the future river streamflow necessary for assessing the flood hazard at the bridge location and (b) simulates the structural behavior of the bridge foundation under sour conditions. In addition, the proposed methodology is used to quantify the reliability of bolted and welded steel connections by integrating finite element analysis and surrogate models. Low-rank tensor approximation and polynomial chaos kriging surrogate models are adopted to perform Monte Carlo simulation and quantify the reliability of the investigated combination connection. Finally, artificial neural networks were used to develop a statistical damage detection and localization approach capable of evaluating the performance of prestressed concrete bridge girders using fiber optic sensors

Structural Health Monitoring Damage Detection Systems for Aerospace

This open access book presents established methods of structural health monitoring (SHM) and discusses their technological merit in the current aerospace environment. While the aerospace industry aims for weight reduction to improve fuel efficiency, reduce environmental impact, and to decrease maintenance time and operating costs, aircraft structures are often designed and built heavier than required in order to accommodate unpredictable failure. A way to overcome this approach is the use of SHM systems to detect the presence of defects. This book covers all major contemporary aerospace-relevant SHM methods, from the basics of each method to the various defect types that SHM is required to detect to discussion of signal processing developments alongside considerations of aerospace safety requirements. It will be of interest to professionals in industry and academic researchers alike, as well as engineering students. This article/publication is based upon work from COST Action CA18203 (ODIN - http://odin-cost.com/), supported by COST (European Cooperation in Science and Technology). COST (European Cooperation in Science and Technology) is a funding agency for research and innovation networks. Our Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation

Smart Sensors for Healthcare and Medical Applications

This book focuses on new sensing technologies, measurement techniques, and their applications in medicine and healthcare. Specifically, the book briefly describes the potential of smart sensors in the aforementioned applications, collecting 24 articles selected and published in the Special Issue “Smart Sensors for Healthcare and Medical Applications”. We proposed this topic, being aware of the pivotal role that smart sensors can play in the improvement of healthcare services in both acute and chronic conditions as well as in prevention for a healthy life and active aging. The articles selected in this book cover a variety of topics related to the design, validation, and application of smart sensors to healthcare