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A BI-Directional Deep Learning Interface for Gaze-Controlled Wheelchair Navigation: Overcoming the Midas Touch Problem
No full textPublisher Copyright: © 2025 IEEE.We present a gaze-based augmented reality control interface for electric wheelchairs, addressing the challenges faced by individuals with mobility impairments. The development transitions through three stages: model training with offline evaluation, Virtual Reality (VR) simulations, and physical deployment. First, we trained deep learning models, comparing Transformers and LSTMs, to predict locomotion intentions based on gaze data. While gaze predicts steering intentions well, it sometimes diverges from locomotion goals. To tackle this, we classify gaze movements as either indicative of locomotor intention or not. This novel approach addresses the Midas Touch Problem of gaze. Datasets were collected in controlled VR environments featuring different tasks. We find that data sets with tasks that encouraged diverse navigation and gaze behaviors enable strong generalization. The online VR simulation evaluation phase enabled safe and immersive testing, allowing the assessment of system performance and the integration of feedback for user guidance. Our approach provided smoother navigation control compared to traditional 'Where-You-Look-Is-Where-You-Go' methods. Feedback improved user ratings of the system. In the final stage, the system was deployed on a physical wheelchair equipped with an augmented reality (AR) device to provide feedback about the predictions to the user, allowing real-world evaluation. Despite differences in user behavior between VR and physical environments, the system successfully translated gaze inputs into precise and safe navigation commands. Users were able to steer the wheelchair solely using their eyes while simultaneously being able to look at destinations at the side of the path.Peer reviewe
Effect of Use of Alkaline Waste Materials as a CO2 Sink on the Physical and Mechanical Performance of Eco-Blended Cement Mortars—Comparative Study
Full text linkPublisher Copyright: © 2025 by the authors.This research paper provides new insights into the impact of accelerated mineralization of alkaline waste materials on the physical and mechanical behavior of low-carbon cement-based mortars. Standardized eco-cement mortars were prepared by replacing Portland cement with 7% and 20% proportions of three alkaline waste materials (white ladle furnace slag, biomass ash, and fine concrete waste fraction) that had been previously carbonated in a static reactor at predefined humidity and CO2 concentration. The mortars’ physical (total/capillary water absorption, electrical resistivity) and mechanical properties (compressive strength up to 90 d of curing) were analyzed, and their microstructures were examined using mercury intrusion porosimetry and computed tomography. The results reveal that carbonated waste materials generate a greater heat of hydration and have a lower total and capillary water absorption capacity, while the electrical resistivity and compressive strength tests generally indicate that they behave similarly to mortars not containing carbonated minerals. Mercury intrusion porosimetry (microporosity) indicates an increase in total porosity, with no clear refinement versus non-carbonated materials, while computed tomography (macroporosity) reveals a refinement of the pore structure with a significant reduction in the number of larger pores (>0.09 mm3) and intermediate pores (0.001–0.09 mm3) when carbonated residues are incorporated that varies depending on waste material. The construction and demolition waste (CCDW-C) introduced the best physical and mechanical behavior. These studies confirm the possibility of recycling carbonated waste materials as low-carbon supplementary cementitious materials (SCMs).Peer reviewe
Gaussian mixture autoencoder for uncertainty-aware damage identification in a floating offshore wind turbine
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Extraordinary sensitivity with quasi-lossy mode resonance mode transition bands in long period fiber gratings
No full textPublisher Copyright: © 2025 Elsevier LtdThis study presents a novel sensor design utilizing a long-period fiber grating (LPFG) deposited with a TiO2 nanocoating via atomic layer deposition. The study combines theoretical simulations and experimental validation to optimize the grating period and modulation index to operate in the mode transition with a quasi-lossy mode resonance (LMR) behavior, i.e., the LPFG attenuation bands shift similarly to LMRs. This enables the achievement of a remarkable sensitivity of 78 nm/nm, allowing for the detection of sub-angstrom variations in film thickness, which is critical for applications in semiconductor manufacturing. Our setup facilitates continuous monitoring of the transmission spectrum, enabling real-time adjustments during deposition to maximize sensitivity. As proof of concept for the applicability of the sensor as a refractive index sensor, we demonstrated exceptional sensitivity for nitrogen detection, achieving around 10,000 nm/RIU, with a figure of merit of 200. This marks one the highest sensitivities reported for optical fiber gas sensors and suggests this technology could revolutionize the field duet to its simplicity in terms of sensor design.Peer reviewe
Comparing Approaches for Predicting Critical Loads in 3D Printed Graphene-reinforced PLA Plates Containing Notches
Full text linkPublisher Copyright: © 2026 The Authors.This work provides a comparison of different methodologies that may be used to estimate critical loads in notched components. The use of 3D-printed composites in structural applications, surpassing the current prototyping application, requires the definition of safe and robust methodologies for the determination of critical loads. Considering that notches (corners, holes, grooves, etc.) are unavoidable in structural components, these stress risers affect the corresponding load-carrying capacity. This study compares the results obtained by applying two different methodologies: the Theory of Critical Distances (TCD) and the Averaged Strain Energy Density (ASED) criterion. Additionally, in the case of TCD, the Line Method, combined with Failure Assessment Diagrams, are used. These methodologies are employed to assess the critical loads in graphene-reinforced polylactic acid (PLA-Gr) plates manufactured by Fused Filament Fabrication with a fixed raster orientation at 45/-45. Furthermore, the plates contain two different notch types (U-notches and V-notches), and comprise various thicknesses (from 5 mm up to 20 mm) and ratios of notch length to plate width (a/W= 0.25 and a/W = 0.50). The comparison between the obtained experimental critical loads and the corresponding estimations derived from the application of the TCD and the ASED reveals that both approaches generate reasonably accurate results, with most of the predictions being safe.Peer reviewe
A methodology for expert knowledge imbrication in mooring system design using Bayesian based optimization
No full textPublisher Copyright: © 2025 The Author(s).Mooring system design optimisation is a complex problem requiring a specific technical expertise. Because of the large number of parameters influencing the design and their related uncertainty, efficient design methodologies and simplified cost models are unavoidable. This study proposes a methodology for the imbrication of expert knowledge on the design optimisation of mooring systems via Bayesian Optimisation (BO). A Gaussian Process Regression has been used as a surrogate model, which is able to estimate both the cost function and the uncertainty of its own predictions. The methodology has been applied to a simplified use case: the design of a three-line simple catenary mooring system. Results show that BO is able to effectively arrive at an optimum solution while providing valuable information about the whole design space, demonstrating potential of the methodology to deal with uncertainties and enable informed decision-making from early design stages.Peer reviewe
D-Wave's Nonlinear-Program Hybrid Solver: Description and Performance Analysis
Full text linkPublisher Copyright: © 2013 IEEE.The development of advanced quantum-classical algorithms is among the most prominent strategies in quantum computing. Numerous hybrid solvers have been introduced recently. Many of these methods are created ad hoc to address specific use cases. However, several well-established schemes are frequently utilized to address optimization problems. In this context, D-Wave launched the Hybrid Solver Service in 2020, offering a portfolio of methods designed to accelerate time-to-solution for users aiming to optimize performance and operational processes. Recently, a new technique has been added to this portfolio: the Nonlinear-Program Hybrid Solver. This paper describes this solver and evaluates its performance through a benchmark of 45 instances across three combinatorial optimization problems: the Traveling Salesman Problem, the Knapsack Problem, and the Maximum Cut Problem. To facilitate the use of this relatively unexplored solver, we provide details of the implementation used to solve these three optimization problems.Peer reviewe
Life cycle assessment of an innovative seabed cleaning platform for marine litter removal in aquatic ecosystems
Full text linkPublisher Copyright: © 2024 The AuthorsPlastic consumption is projected to rise significantly over the coming decades, especially in developing economies, leading to increased plastic leakage into the environment and the accumulation of waste in ecosystems. Despite the urgent need to address this issue, the environmental implications of marine litter removal technologies have been largely unexplored. This paper addresses this gap by presenting the first comprehensive Life Cycle Assessment (LCA) of the Seabed Cleaning Platform, a novel cable-based underwater robot developed by TECNALIA to remove litter selectively and efficiently from the seabed and lower water column. The Seabed Cleaning Platform introduces significant advancements in marine litter removal by enabling a more efficient and cost-effective process. Its innovative design allows for selective and automated removal of identified debris, ranging from microplastics (>5 mm) to large items. Additionally, the system is designed to operate in a manner that benefits the marine ecosystem, mitigating the environmental impact of traditional clean-up efforts. The LCA provides an in-depth evaluation of the platform's environmental performance throughout its entire life cycle. Results indicate that the use and maintenance phases account for 70.9 % of the total environmental impact. Sensitivity analyses highlight optimization opportunities, such as increasing operational time and waste collection volume to reduce the environmental impact per unit of waste removed and replacing the generator with a smaller, more efficient model to minimize fuel consumption. This study marks an important step in applying LCA to emerging marine litter removal technologies. Unlike analyses focused exclusively on operational efficiency, this research quantifies the environmental trade-offs and scalability potential of the Seabed Cleaning Platform. These insights provide valuable information for improving the environmental performance of marine litter removal technologies and guide future developments in this field.Peer reviewe
Integrative assessment of hydrogen-natural gas mixtures in energy grids: An overview of the H2SAREA project experience
Full text linkPublisher Copyright: © 2025 The AuthorsThis paper presents the results of the H2SAREA project, which focuses on integrating hydrogen (H2) into the existing natural gas (NG) distribution network, with blends of up to 20%. A key component of the project was the H2Loop testing platform, built using ex-service materials and components to realistically assess the impact of hydrogen on current systems and components. The investigation covered several critical areas, including gas injection and blending, network capacity, leak detection, gas pressure regulation station (GPRS) performance, valve and meter functionality, materials compatibility, permeation testing, and gas deblending. Results show the feasibility of safely injecting up to 20% hydrogen into the existing system, offering valuable insights to guide the transition of gas distribution networks toward a hydrogen-based energy future.Peer reviewe
Fire Safety of Steel Envelope Systems with Bio-Based Insulation: Evaluation of Smoldering Phenomenon
Full text linkPublisher Copyright: © 2025 by the authors.The use of innovative insulating materials can contribute to an energy-efficient design by improving the thermal performance of building envelopes while also reducing the embodied energy of materials. Ultra-low carbon steel envelope solutions with bio-based insulations are aligned with this approach. However, fire safety aspects in general and smoldering issues in particular need to be considered when using bio-based insulations. Accordingly, this paper proposes a system-level assessment of the fire performance of steel envelopes with bio-based insulations, not only identifying potential smoldering issues of the core material but also defining and evaluating strategies that could address these concerns within the system design. For this purpose, the variables that could affect the fire performance of wood fiber insulation sandwich panels were identified while considering the different stages of the smoldering phenomena, such as the influence of the joint design or mounting provisions for the initiation, the existence of air cavities, oxygen entrances or physically continuous materials with a tendency to smolder for the continuation, or the inclusion of limiting elements or mitigation layers for spread limitation. Finally, strategies for fire-safe enclosures using bio-based insulations are proposed, assuming smoldering affections in wood-derived materials and analyzing possible mitigation elements at the system level.Peer reviewe