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Prediction of wind turbines power with physics-informed neural networks and evidential uncertainty quantification
No full textPublisher Copyright: © 2025 Elsevier Ltd.The ever-growing use of wind energy requires the optimization of turbine operations through pitch angle controllers and early fault detection. Accurate and robust models that replicate turbine behavior are essential, particularly for predicting generated power from wind speed. Existing empirical and physics-based models often fail to capture the complex relationships between input variables and power output, aggravated by wind variability. Data-driven methods offer promising alternatives by improving model accuracy and scalability with large datasets. In this study, we use physics-informed neural networks to model historical data from four turbines in a wind farm, embedding physical constraints into the learning process. The proposed models predict power, torque, and power coefficient with high accuracy for both the data and the governing physical laws. Notably, neural networks improve the prediction of the power coefficient by an order of magnitude over empirical models. Physics-informed neural networks also show higher robustness than standard networks under limited data, maintaining accuracy even when trained on reduced datasets. Finally, the inclusion of an evidential layer provides uncertainty estimations that align with absolute errors and allow confidence intervals on the power curve, ensuring consistency with both observed data and manufacturer specifications.Peer reviewe
Hydrogen peroxide-based oxidation and pH-controlled precipitation for the recovery of non-cerium rare earth elements from permanent magnet waste
Full text linkPublisher Copyright: © 2025 The AuthorsThis case study presents a sustainable and scalable process for the recovery of non-cerium rare earth elements (non-Ce REE) from end-of-life neodymium–iron–boron (NdFeB) permanent magnets. The method involves the selective precipitation of cerium using hydrogen peroxide at pH 5.5 and a NaOH/REE weight ratio between 0.41 and 0.45. Under these conditions, cerium was effectively removed from the leachate with a precipitation yield exceeding 99 wt%. The resulting cerium-based precipitate was calcined at 900 °C, and subsequent leaching in 1 M HCl enabled the recovery of non-Ce REE, including neodymium, praseodymium, gadolinium and dysprosium, with a maximum recovery rate of 97.9 wt%. The cerium content in the final product was controlled between 0.07 wt% and 2.1 wt% by adjusting the precipitation temperature, allowing for the production of two distinct rare earth oxide streams. The process was validated using real leachates obtained from the recycling of industrial magnet waste, demonstrating its applicability in real-world scenarios. The use of environmentally benign reagents and well-established unit operations supports the industrial feasibility and environmental sustainability of the proposed method. The results highlight the potential of this approach for the recovery of critical raw materials in line with circular economy and decarbonisation goals, offering a viable solution for the sustainable management of rare earth resources in industrial recycling contexts.Peer reviewe
Applicability and accuracy of physical CO2 mass balance in multi-zone mechanically ventilated office buildings to estimate real-time occupancy
Full text linkPublisher Copyright: © 2025 The Author(s)Accurate real-time occupancy estimation in office buildings is crucial for efficient system control and security. While AI-based methods have recently gained prominence, this study revisits the physical CO2 mass balance approach, traditionally applied to simpler environments, by evaluating its performance in a complex multi-zone mechanically ventilated office with high occupancy. A detailed sensitivity analysis identified the change in indoor CO2 concentration as the most influential variable, guiding the application of smoothing filters. A vision-based ground truth dataset over 25 days enabled rigorous model validation using various error indicators. The best-performing model, using an Exponential Moving Average filter with a 0.9 smoothing factor and 10-minute data averaging, achieved a Mean Absolute Error of 1.56 persons and Root Mean Square Error of 2.98 persons—under 10 % of the maximum recorded occupancy. However, it tended to overestimate during unoccupied hours due to sensitivity to minor CO₂ fluctuations. With a five-person tolerance, the model achieved over 90 % accuracy, demonstrating practical applicability for system control. Model variations, including rounding and enhanced variable monitoring, further improved results. The study confirms that indoor CO2 measurement quality is critical, particularly sensor placement. During working hours, the model reliably detects presence but struggles with exact occupancy. Compared to AI models, this approach is simpler, does not require training, and is broadly applicable where relevant variables are monitored. Future work will explore sensor layout optimisation and dynamic variables like outdoor CO2. Overall, the CO2 mass balance remains a viable, low-complexity alternative for occupancy estimation in multi-zone offices.Peer reviewe
Complex IV deficiency due to COX4I1 deep intronic and de novo variants results in progressive motor impairment and Leigh syndrome
No full textPublisher Copyright: © 2025 The Author(s)COX4I1 gene encodes cytochrome c oxidase subunit 4 isoform 1, involved in the early assembly stages of mitochondrial respiratory chain complex IV. To date, COX4I1 pathogenic variants have been reported in only a few cases, each exhibiting heterogeneous clinical phenotypes and limited functional data. Here, we describe the fourth reported case of COX4I1 deficiency associated with human disease, expanding the phenotypic and genetic spectrum of this rare mitochondrial disorder and providing novel clinical, molecular, and functional data. The herein reported individual presented with progressive deterioration of motor skills, intellectual disability and brain imaging abnormalities compatible with Leigh syndrome. Genetic studies combining short and long read next generation sequencing uncovered a peculiar genetic combination in this patient, harboring a de novo COX4I1 nonsense substitution in trans with an inherited deep intronic variant (c.[64C>T];[73+1511A>G]; p.[Arg22Ter];[Glu25ValfsTer9]). Functional studies performed in patient's tissues and transiently transfected cell lines demonstrated that the identified variants mainly exert their pathogenic effect by targeting COX4I1 protein levels, thereby impairing the proper assembly and activity of complex IV. Additionally, proteomic data in patient's fibroblasts suggested an underlying pathomechanism that involves not only the regulation of complex IV function but also the levels of mitoribosomal proteins. In summary, our findings shed light to clarify some of the main clinical features associated with COX4I1 deficiency and the molecular mechanisms involved in the pathogenesis of this disorder.Peer reviewe
High-Fidelity Coherent-One-Way QKD Simulation Framework for 6G Networks: Bridging Theory and Reality
Full text linkPublisher Copyright: © 2004-2012 IEEE.Quantum key distribution (QKD) has emerged as a promising solution for guaranteeing information-theoretic security. Inspired by this, a great amount of research effort has been recently put on designing and testing QKD systems as well as articulating preliminary application scenarios. However, due to the considerable high-cost of QKD equipment, a lack of QKD communication system design tools, wide deployment of such systems and networks is challenging. Motivated by this, this paper introduces a QKD communication system design tool. First we articulate key operation elements of the QKD, and explain the feasibility and applicability of coherent-one-way (COW) QKD solutions. Next, we focus on documenting the corresponding simulation framework as well as defining the key performance metrics, i.e., quantum bit error rate (QBER), and secrecy key rate. To verify the accuracy of the simulation framework, we design and deploy a real-world QKD setup. We perform extensive experiments for three deployments of diverse transmission distance in the presence or absence of a QKD eavesdropper. The results reveal an acceptable match between simulations and experiments rendering the simulation framework a suitable tool for QKD communication system design.Peer reviewe
A comprehensive review of thermal energy storage technologies and their applications: Creation of a database
Full text linkPublisher Copyright: © 2025 The AuthorsThermal energy storage (TES) stands out as a key solution for advancing energy conservation and enhancing system efficiency, especially when paired with local renewable energy sources (RES). As the global shift toward sustainability accelerates, TES technologies hold the potential to play a central role in mitigating the challenges posed by increasing energy demands. However, despite its demonstrated efficacy and promise, TES has not yet achieved widespread adoption. This gap underscores the need for greater collaboration among experts, coupled with initiatives to raise public awareness and enhance education on the benefits and applications of TES. In this review, we take a comprehensive approach to explore the latest developments in TES systems, with a specific focus on their integration with renewable energy and HVAC&R applications. In addition, this review includes a comparative analysis of TES technologies focusing on costs, environmental aspects and selection criteria. This work's main objective is to provide an in-depth analysis of TES technologies and to create a valuable resource for the renewable energy community. To this end, we have compiled a detailed and structured dataset that categorizes TES technologies by type and forms the foundation of a unique, user-friendly database. A key innovation of this review is the creation of a dynamic online platform that offers free and open access to this database. Built using “Looker Studio,” the platform provides a seamless, interactive experience where users can easily search and filter information based on TES type, application, temperature range, efficiency, lifetime, and other relevant parameters. This continuously updated database addresses the long-standing need for a centralized, accessible repository of TES information, offering researchers, industry professionals, and stakeholders a powerful tool for informed decision-making. This novel platform distinguishes our review from previous studies by making the vast landscape of TES technologies not only more accessible but also adaptable to the specific needs of users. By offering this free, searchable resource to the renewable energy community, we aim to facilitate the adoption of TES technologies and support the global transition toward sustainable energy solutions.info:eu-repo/grantAgreement/EC/HE/101096368/EU/EFFICIENT COMPACT MODULAR THERMAL ENERGY STORAGE SYSTEM/ECHOPeer reviewe
Sensitivity enhancement of a lossy mode resonance immunosensor using gold-nanoparticles for the detection of vascular endothelial growth factor protein
No full textPublisher Copyright: © 2025 Elsevier B.V.While the transition from optical fiber to planar waveguide substrates in LMR-based sensors has allowed for the development of more robust, cost-effective, and easily manufactured platforms, it has also presented challenges in optimizing critical sensor parameters such as resolution and sensitivity in biosensing. In this work, we introduce the application of gold nanoparticles (AuNP) to enhance the sensitivity of a Lossy Mode Resonance (LMR)-based biosensor for the detection of vascular endothelial growth factor (VEGF) protein. The sensor was developed by depositing a nanometric TiO2 film on a planar waveguide, and its performance was assessed using three detection approaches: label-free, sandwich assay, and AuNP-labeled sandwich assay. The integration of AuNP significantly improved sensitivity, enabling detection at concentrations as low as 0.1 ng mL−1, surpassing the sensitivity of traditional label-free LMR-based sensors. These results demonstrate the potential of AuNP-enhanced LMR sensors for detecting low concentrations of biomarkers with high specificity and sensitivity, positioning them as promising tools for biosensing applications.Peer reviewe
Analysis of the Difference Between the Reference Temperature Values Derived From Conventional and Mini-C(T) Specimens: Effect of the Number of Valid Fracture Tests
No full textPublisher Copyright: Copyright © 2026 by ASME.The long-term-operation of nuclear power plants (NPPs) requires a precise knowledge of the fracture toughness of the reactor pressure vessel (RPV) materials. This property decreases with the irradiation level, so surveillance programs measure it throughout the NPP operational life by testing materials placed inside the RPV which were initially designed to cover the initial lifespan. Therefore, the amount of available material to be tested during the life extension of NPPs may be scarce, and it is not possible to perform fracture tests using conventional specimens (e.g., 1T or 25.4 mm thick). In this context, mini-C(T) specimens (0.16T) appear as a key technology. Generally, mini-C(T) specimens provide similar results to those generated by using conventional specimens. However, there are situations where the deviations between the T0 predictions of conventional and mini-C(T) specimens are negligible, and situations where such deviations are as high as 40C. This work provides a comprehensive literature review of experimental T0 results obtained using conventional fracture specimens and mini-C(T) specimens, analyzing how the corresponding deviations are affected by the number of valid tests used to define T0. The research includes a total of 140 datasets, covering base, heat affected zone (HAZ), and weld materials, and both irradiated and unirradiated conditions. With all this, the paper finally provides insights into how the mentioned deviations depend on the extent of the experimental program performed for the characterization of T0, revealing that larger experimental programs tend to provide smaller discrepancies.Peer reviewe
Towards Collective Perception Hybrid Testing in a Roundabout Scenario with AVs
Full text linkPublisher Copyright: © The Author(s) 2026.Collective Perception (CP) allows connected autonomous vehicles to share and fuse processed sensor data via V2X communication. It can potentially allow for an increased object update rate, extended field-of-view awareness, and redundancy but it first requires a thorough evaluation and validation. Due to the CP’s field testing practical challenges most of the previous work on CP has considered large scale-simulations with a focus on connectivity/network aspects. More recently, large-scale collaborative perception synthetic datasets and open source benchmarks have appeared, allowing the perception engineers to study CP from a perception point of view, which is missing so far. In this paper, the first building blocks (work in progress) towards CP scenario-based testing for a roundabout navigation use case are been set by proposing a Bayesian CP algorithm and its testing plan. The CP algorithm is described and metrics for CP assessment are discussed focusing on the fused information content produced by the algorithm. The next steps towards a hybrid evaluation plan combining real-world agents and simulation are outlined.Peer reviewe
Methodologies in digital twin for manufacturing industry: A systematic literature review
No full textPublisher Copyright: © 2025 The Author(s)In recent years, the investigation of methodologies pertaining to the application of digital twins within the industrial sector has garnered significant interest. This increased development is attributed to the challenges associated with the sustainable design, development, and implementation of such solutions. This study undertakes a systematic review of the literature, encompassing entries from three prominent databases over the past five years. Consequently, the study analyzes step-by-step methodologies, both generalist and specific to particular domains and applications. The paper commences with a brief introduction and presentation of foundational concepts, followed by an exploration of related works and the methodology employed in this research. The study proceeds with detailed sections dedicated to each analyzed methodology, culminating in a discussion and conclusion section that underscore the increasing interest in the development of novel methodologies for the design and implementation of digital twins. Despite the growing volume of research in this domain, a significant proportion of the literature lacks comparative analyses of the benefits, advantages, and limitations associated with different methodological approaches. Furthermore, many of these studies remain largely theoretical or are confined to narrowly defined use cases, with limited evidence of practical, real-world application. The review concludes that digital twins constitute complex systems comprising real, digital, virtual, and conceptual components. It also highlights those numerous methodologies, originally developed in other disciplines, possess the potential to be adapted to support the development and deployment of digital twin systems.Peer reviewe