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Continuous carbon fiber Additive Preforming and its application for the fabrication of epoxy composites
Get PDFPublisher Copyright: © 2025 Society of Plastics Engineers.This study presents Additive Preforming, a novel technique for manufacturing continuous fiber-reinforced polymer composites. The new technique consists of 3D printing continuous fiber filaments coated with a suitable thermoplastic for the fabrication of continuous fiber preforms. These preforms can eventually be used to produce thermoset composite parts. The manufacturing technology used here to produce epoxy-carbon composites involved coating a continuous carbon fiber roving with a thermoplastic polymer (binder) to produce a 3D-printable filament. This filament was then 3D-printed to create a preform, and the final composite was obtained by impregnating the preform with the epoxy matrix. To optimize the final properties of the epoxy-carbon composite, a screening protocol for potential thermoplastic binders was developed and implemented. This protocol aimed to identify the most compatible/miscible binders for the epoxy resin. The evaluation was conducted using Hansen's solubility parameters, interfacial tension determinations, and optical microscopy observations. The results identified polycarbonate (PC) and phenoxy resin (PH) as the most suitable candidates. The mechanical properties of the composites were strongly influenced by the binder used, and the best properties (elastic modulus of 32 GPa and flexural strength of 609 MPa) were achieved when PH was used. The carbon fiber content of the composites was also optimized by comparing the mechanical properties of the composites obtained with 12 and 24 k carbon fibers. The resulting epoxy composites – made of phenoxy-coated continuous carbon fibers and containing approximately 40 wt% of carbon fibers – featured an elasticity modulus of 62 GPa and flexural strength of 852 MPa. Highlights: Additive Preforming is proposed for manufacturing CFPCs. Continuous carbon fiber is coated and 3D-printed prior to impregnation in epoxy. The established screening protocol ranks binders based on their compatibility. PH was identified as the optimum binder and was validated by mechanical tests. The optimization of the fiber content led to superior mechanical properties.Peer reviewe
Reviewing experimental studies on latent thermal energy storage in cementitious composites: report of the RILEM TC 299-TES
No full textPublisher Copyright: © The Author(s), under exclusive licence to RILEM 2025.In recent years, substantial progress has been achieved in the development of multifunctional cement-based composites, targeting improved energy efficiency and environmental sustainability while minimizing material depletion. Leveraging the high thermal capacity of these materials facilitates controlled heat storage and release, providing versatile applications in renewable energy management and heat regulation, influencing structural integrity and long-term resistance. Recent research has integrated phase change materials (PCMs) into these composites to harness their superior thermal energy density. This comprehensive review examines the latest experimental research findings on these hybrid materials, emphasizing their thermo-physical behaviour and influence on structural properties and durability. Furthermore, it provides an overview of PCM characteristics and their integration into cement-based matrices. It critically analyses the interaction between PCMs and the cement matrix, explaining effects on structural performance, hydration processes, and freeze–thaw mechanisms. Furthermore, the paper explores recent experimental techniques and protocols for measuring and assessing the structural and thermo-physical properties of these composites. By identifying key trends, the review aims to provide valuable insights into the design and optimization of cement-based composites with PCMs, ultimately enhancing energy efficiency and resource conservation.Peer reviewe
Corrigendum to “A life cycle assessment model to evaluate the environmental sustainability of lignin-based polyols” [Sustain. Prod. Consump. 52 (2024) 624–639, (S2352550924003312), (10.1016/j.spc.2024.11.019)]
Get PDFPublisher Copyright: © 2024 The Author(s)The authors regret missing the Acknowledgement
Haptic Icons: A Hands-On Approach to Haptic HMI in Automated Vehicles
Get PDFPublisher Copyright: © 2020 IEEE.This paper examines the potential integration of haptic feedback on steering wheels for automated driving applications, with a particular focus on transitions between automated and manual modes, takeover requests, and warnings. An iterative, three-phase methodology was employed: (1) The initial set of haptic notifications was designed based on input from the literature review, (2) These notifications were then tested in a driving simulator to identify the most effective options, and (3) The selected notifications were evaluated in a dynamic simulator under realistic conditions, including noise, vibration, and harshness (NVH). User studies were conducted at each phase to gather subjective metrics and validate the usability of the haptic feedback. The results demonstrate that specific haptic patterns enhance driver situational awareness and improve transitions between driving modes compared to conventional auditory signals, contributing to safer human-machine interaction in automated vehicles.Peer reviewe
Evaluation of PTSO delivery approaches for gut microbiota modulation in colorectal cancer: A comparative study of microcapsules containing Allium derivatives
Get PDFPublisher Copyright: © 2025 The AuthorsColorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide, with gut microbiota modulation emerging as a critical factor in its development. Propyl propane thiosulfonate (PTSO), an organosulfur compound derived from Allium species, has shown potential as a therapeutic agent for CRC due to its antioxidant and anti-inflammatory properties. This study evaluated three PTSO delivery systems (dextrin, pectin microcapsules, and hydroxypropyl methylcellulose capsules) designed to enhance bioavailability and protect PTSO through digestion. We assessed their antioxidant capacity, cytotoxic effects on CRC cells, and impact on short-chain fatty acid (SCFA) production and gut microbiota composition after in vitro digestion and fermentation with feces of healthy individuals and CRC patients. Results demonstrated that each formulation displayed distinct release profiles and antioxidant activities post-digestion and fermentation, with microencapsulated PTSO showing superior stability, bioavailability and the highest antitumoral efficacy in CRC cell lines, achieving an IC50 value of 20.5 μM. Significant differences in SCFA production and gut microbiota modulation were observed across the formulations. Although further in vivo studies are needed to validate these findings and understand long-term effects, PTSO shows promise as a bioactive compound within functional nutrition. Its ability to modulate gut microbiota composition, alongside its enhanced bioavailability through innovative delivery systems, suggests that PTSO could play a key role in the development of dietary strategies aimed at reducing CRC risk and progression.Peer reviewe
Protective Ti sub-oxide coatings on proton exchange water electrolysis prepared by HiPIMS technology
Get PDFPublisher Copyright: © 2025 The AuthorsElectrolysis, the process of splitting water into hydrogen and oxygen using electrical current, stands as a pivotal technology in the current hydrogen economy. Among various electrolyser technologies, proton exchange membrane water electrolysers (PEMWEs) are favored for their high efficiency, durability, and suitability for commercial applications. However, the cost of PEMWE systems, particularly the bipolar plates (BPs), which account for ∼25 % of system costs, remains a critical challenge. Stainless steel BPs has been explored as a cost-effective alternative to titanium BPs, but they require protective coatings to prevent corrosion under PEMWE conditions. This study focuses on developing titanium suboxide (Ti sub-oxide) coatings for stainless steel BPs to enhance corrosion resistance, maintaining a moderate contact resistance. Ti sub-oxide coatings were deposited using High-Power Impulse Magnetron Sputtering (HiPIMS), a technique enabling high-density and homogeneous material deposition. Key strategies to increase coating compactness, including substrate polarization and cyclic ion bombardment during deposition, were investigated. Morphological and compositional analyses were conducted, along with evaluations of corrosion resistance and electrical performance. The results demonstrate that Ti sub-oxide coatings developed with the selected approaches, exhibit improved compactness, which could potentially limit electrolyte infiltration, enhancing the durability and performance of stainless steel substrates. These findings highlight the promising behavior of Ti sub-oxide coatings under harsh PEMWE conditions. While further studies are needed in actual PEM electrolyzers, they suggest a cost-effective solution for advancing PEMWE technology and green hydrogen scalability toward Net Zero goals.Peer reviewe
Combining physics-based and data-driven methods in metal stamping
No full textPublisher Copyright: © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.This work presents a methodology for combining physical modeling strategies (FEM), machine learning techniques, and evolutionary algorithms for a metal stamping process to ensure process quality during production. Firstly, a surrogate model or metamodel is proposed to approximate the behavior of the simulation model for different outputs in a fraction of time. Secondly, based on the surrogate model, multiple soft sensors that estimate different quality measures of the stamped part departing from the draw-ins are proposed, which enables their integration into the process. Lastly, evolutionary algorithms are used to estimate the latent blank characteristics and for the prescriptions of process parameters that maximize the quality of the stamped part. The obtained numerical results are promising, with relative errors around 2 2% in most cases and outperforming a naive method. This methodology aims to be a decision support system that moves towards zero defects in the stamping process from the process conception phase.Peer reviewe
Definition, estimation and decoupling of the overall uncertainty of the outdoor air temperature measurement surrounding a building envelope
Get PDFPublisher Copyright: © The Author(s) 2024.Outdoor air temperature represents a fundamental physical variable that needs to be considered when characterising the energy behaviour of buildings and its subsystems. Research, for both simulation and monitoring, usually assumes that the outdoor air temperature is homogeneous around the building envelope, and when measured, it is common to have a unique measurement representing this hypothetical homogeneous outdoor air temperature. Furthermore, the uncertainty associated with this measurement (when given by the research study) is normally limited to the accuracy of the sensor given by the manufacturer. This research aims to define and quantify the overall uncertainty of this hypothetical homogeneous outdoor air temperature measurement. It is well known that there is considerable variability in outdoor air temperature around the building and measurements are dependent on the physical location of outdoor air temperature sensors. In this research work, this existing spatial variability has been defined as a random error of the hypothetical homogeneous outdoor air temperature measurement, which in turn has been defined as the average temperature of several sensors located randomly around the building envelope. Then, some of these random error sources which induce spatial variability would be the cardinal orientation of the sensor, the incidence of solar radiation, the outdoor air temperature stratification, the speed and variations of the wind and the shadows of neighbouring elements, among others. In addition, the uncertainty associated with the systematic errors of this hypothetical homogeneous outdoor air temperature measurement has been defined as the Temperature Sensor Uncertainty (Formula presented.) where this uncertainty is associated with the sensor’s accuracy. Based on these hypotheses, a detailed statistical procedure has been developed to estimate the overall Temperature Uncertainty (Formula presented.)) of this hypothetical homogeneous outdoor air temperature measurement and the Temperature Sensor Uncertainty (Formula presented.). Finally, an uncertainty decoupling method has also been developed that permits the uncertainty associated with random errors (Temperature’s Spatial Uncertainty (Formula presented.)) to be estimated, based on (Formula presented.) and (Formula presented.) values. The method has been implemented for measuring the outdoor air temperature surrounding an in-use tertiary building envelope, for which an exterior monitoring system has been designed and randomly installed. The results show that the overall Temperature Uncertainty (Formula presented.) for the whole monitored period is equal to ±2.22°C. The most notable result is that the uncertainty associated with random errors of measurement (Temperature’s Spatial Uncertainty (Formula presented.)) represents more than 99% of the overall uncertainty; while the Temperature Sensor Uncertainty (Formula presented.), which is the one commonly used as the overall uncertainty for the outdoor air temperature measurements, represents less than 1%.Peer reviewe
Wood-for-construction supply chain digital twin to drive circular economy and actor-based LCA information
Get PDFPublisher Copyright: © 2025 The AuthorsThe integration of Digital Twin (DT) technologies and Life Cycle Assessment (LCA) in the construction sector presents significant opportunities for improving resource efficiency, enhancing material traceability, and supporting circular economy strategies. However, the lack of standardized methodologies and data interoperability remains a major barrier to effective implementation. This study introduces the Forest to Building Digital Framework (F2BDF), a structured approach that combines DT technologies, actor-based LCA, and supply chain management digital tools to optimize the environmental performance of wood construction. The research is among the earliest to develop a digital system throughout the life cycle from the extraction of raw materials to the construction. The framework is built on a hierarchical structure where digitalized different actors’ subsystems within the supply chain generate real-time production data, feeding into a centralized backbone network. These data are the foundation for a decision support module designed to assess environmental impacts and evaluate circularity scenarios. The study integrates geospatial analysis (GIS), real-time manufacturing data (CAx and BIM), and digital product information. The validation process in an industrial setting exhibits how enhanced data integration can support real-time sustainability assessments with primary foreground data and optimize resource utilization. The results included enhanced material circularity options, data portability, and building materials tracking, as well as semi-automatically contributing to achieving more dynamic and actor-based LCA information. By digitizing multiple stakeholders and making product, production, and transportation data accessible via APIs (Application Programming Interfaces), widespread digital frameworks can offer a scalable solution for improving sustainability across the wood construction sector.Peer reviewe
Diverse policy generation for the flexible job-shop scheduling problem via deep reinforcement learning with a novel graph representation
Get PDFPublisher Copyright: © 2024 The AuthorsIn scheduling problems common in the industry and various real-world scenarios, responding in real-time to disruptive events is important. Recent methods propose the use of deep reinforcement learning (DRL) to learn policies capable of generating solutions under this constraint. However, current DRL approaches struggle with large instances, which are common in real-world scenarios. The objective of this paper is to introduce a new DRL method for solving the flexible job-shop scheduling problem, with a focus on these type of instances. The approach is based on the use of heterogeneous graph neural networks to a more informative graph representation of the problem. This novel modeling of the problem enhances the policy's ability to capture state information and improve its decision-making capacity. Additionally, we introduce two novel approaches to enhance the performance of the DRL approach: the first involves generating a diverse set of scheduling policies, while the second combines DRL with dispatching rules (DRs) constraining the action space, with a variable degree of freedom depending on the chosen policy. Experimental results on two public benchmarks show that our approach outperforms DRs and achieves superior results compared to three state-of-the-art DRL methods, particularly for large instances.Peer reviewe