Abstract
Structural health monitoring (SHM) of reinforced concrete structures (RCS) is crucial for mitigating the consequences of their deterioration. By identifying and addressing the issues early, SHM helps reduce environmental impact, safeguard lives, and enhance economic resilience. Rebar corrosion is a leading cause of early RCS decay and optical fibre sensors (OFS) have been employed for its monitoring. Reflection optrodes using optical fibres where the tip is coated with iron (Fe) thin films offer a robust, long-lasting and straightforward solution. This study investigates the tracking of spectral changes during the Fe thin film corrosion, which has been neglected in the literature, in favour of tracking reflection changes from thin film spalling. A multimode fibre tip, coated with a thin Fe layer embedded in concrete, allows spectral changes to be observed during corrosion. A 100 nm thick Fe film was deposited using radio frequency magnetron sputtering on polished fibre tips. Corrosion was induced by applying salted water drops and allowing the fibre tip to dry. Corrosion monitoring was successful for both air-exposed and cement-embedded tips, with results compared to reflection simulations of Fe, Fe2O3, and Fe2O3 thin films. This study supports monitoring at different wavelengths, enhancing robustness, cost-effectiveness and earlier detection. © The Authors.

Abstract
Active distribution networks (ADNs) are consistently being developed as a result of increasing penetration of distributed energy resources (DERs) and energy transition from fossil-fuel-based to zero carbon era. This penetration poses technical challenges for the operation of both transmission and distribution networks. The determination of the active/reactive power capability of ADNs will provide useful information at the transmission and distribution systems interface. For instance, the transmission system operator (TSO) can benefit from reactive power and reserve services which are readily available by the DERs embedded within the downstream ADNs, which are managed by the distribution system operator (DSO). This article investigates the important factors affecting the active/reactive power flexibility area of ADNs such as the joint active and reactive power dispatch of DERs, dependency of the ADN's load to voltage, parallel distribution networks, and upstream network parameters. A two-step optimization model is developed which can capture the P/Q flexibility area, by considering the above factors and grid technical constraints such as its detailed power flow model. The numerical results from the IEEE 69-bus standard distribution feeder underscore the critical importance of considering various factors to characterize the ADN's P/Q flexibility area. Ignoring these factors can significantly impact the shape and size of Active Distribution Networks (ADN) P/Q flexibility maps. Specifically, the Constant Power load model exhibits the smallest flexibility area; connecting to a weak upstream network diminishes P/Q flexibility, and reactive power redispatch improves active power flexibility margins. Furthermore, the collaborative support of reactive power from a neighboring distribution feeder, connected in parallel with the studied ADN, expands the achievable P/Q flexibility. These observations highlight the significance of accurately characterizing transmission and distribution network parameters. Such precision is fundamental for ensuring a smooth energy transition and successful integration of hybrid renewable energy technologies into ADNs. The article investigates factors influencing the flexibility of active distribution networks (ADNs), including joint active and reactive power re-dispatch of DERs, ADN's load model, parallel distribution networks, and upstream network parameters. Numerical results highlight the significance of these factors, emphasizing the need for accurate characterization of transmission and distribution network parameters to facilitate a smooth energy transition and the integration of hybrid renewable energy technologies into ADNs. image

Abstract
The integration of Distributed Energy Resources (DER) imposes challenges to the operation of distribution networks. This paper conducts a systematic assessment of the impact of DER on distribution network overcurrent protection, considering the behavior of Inverter Based Resources (IBR) during faults in the coordination of medium voltage (MV) feeders' overcurrent protection. Through a detailed analysis of various scenarios, we propose adaptive protection solutions that enhance the reliability and resilience of distribution networks in the face of growing renewable energy integration. Results highlight the advantages of using adaptive protection over traditional methods and topology changes, and delve into current protection strategies, identifying limitations and proposing mitigation strategies. © The Institution of Engineering & Technology 2024.

Abstract
The assessment of deposited material in tunnel reinforcement operations can be performed using a 3D model generated from multiple scans. For this purpose, an accurate alignment of the scanned models is required. Aligning existing structure model with data scanned after surface deformations can be challenging, particularly if reference markers are not available or were displaced. For scenarios where the surrounding structure is largely changed, certain procedures can be adapted when processing the scanned data to achieve consistent alignment between scanned and reference structure models. This work proposes a methodology to cope with these situations, analysing the impact of different approaches. Experiments were performed in a realistic scenario related with shotcrete of railway tunnels wall surfaces, with the results showing the applicability of the developed work. The proposed procedure relies in highlighting the importance of specific points that describe the same feature in the reference and aligning PC. The proposed methodology achieved an RMS difference of 0.0173 m, which lead to a drastic improvement in the point cloud alignment compared to the use of standard ICP algorithm without data preprocessing, which achieved 0.0518 m in the studied use-case.

Abstract
While a significant number of databases are deployed in cloud environments, pushing part or all data storage and querying planes closer to their sources (i.e., to the edge) can provide advantages in latency, connectivity, privacy, energy, and scalability. This article dissects the advantages provided by databases in edge and fog environments by surveying application domains and discussing the key drivers for pushing database systems to the edge. At the same time, it also identifies the main challenges faced by developers in this new environment and analyzes the mechanisms employed to deal with them. By providing an overview of the current state of edge and fog databases, this survey provides valuable insights into future research directions.

Abstract
Nanoparticle-based plasmonic optical fiber sensors can exhibit high sensing performance, in terms of refractive index sensitivities (RISs). However, a comprehensive understanding of the factors governing the RIS in this type of sensor remains limited, with existing reports often overlooking the presence of surface plasmon resonance (SPR) phenomena in nanoparticle (NP) assemblies and attributing high RIS to plasmonic coupling or waveguiding effects. Herein, using plasmonic optical fiber sensors based on spherical Au nanoparticles, we investigate the basis of their enhanced RIS, both experimentally and theoretically. The bulk behavior of assembled Au NPs on the optical fiber was investigated using an effective medium approximation (EMA), specifically the gradient effective medium approximation (GEMA). Our findings demonstrate that the Au-coated optical fibers can support the localized surface plasmon resonance (LSPR) as well as SPR in particular scenarios. Interestingly, we found that the nanoparticle sizes and surface coverage dictate which effect takes precedence in determining the RIS of the fiber. Experimental data, in line with numerical simulations, revealed that increasing the Au NP diameter from 20 to 90 nm (15% surface coverage) led to an RIS increase from 135 to 6998 nm/RIU due to a transition from LSPR to SPR behavior. Likewise, increasing the surface coverage of the fiber from 9% to 15% with 90 nm Au nanoparticles resulted in an increase in RIS from 1297 (LSPR) to 6998 nm/RIU (SPR). Hence, we ascribe the exceptional performance of these plasmonic optical fibers primary to SPR effects, as evidenced by the nonlinear RIS behavior. The outstanding RIS of these plasmonic optical fibers was further demonstrated in the detection of thrombin protein, achieving very low limits of detection. These findings support broader applications of high-performance NP-based plasmonic optical fiber sensors in areas such as biomedical diagnostics, environmental monitoring, and chemical analysis. (c) 2024 Chinese Laser Press