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Numerical assessment of the high cycle fatigue behavior of high strength steels affected by shear-cutting operations
No full textShear-cutting processes are arguably among the most preferred technologies for performing material removal operations in the manufacturing of chassis components due to the combination of high production rate and cost-efficiency. Nevertheless, they may severely jeopardize the fatigue response of high strength metals, compromising the current trend of using this class of materials for weight reduction of automotive chassis parts. Thus, the generation of reliable data featuring the influence of these operations on the material fatigue behavior is essential to further support this lightweighting tendency. Commonly employed for this aim, traditional fatigue tests are usually time-consuming and rather expensive. In this context, numerical simulations arise as a viable alternative, providing not only material-related information but also assisting engineers in the design of new components. In this work, an isotropic damage-based high cycle fatigue model is employed to estimate the fatigue life of trimmed and punched specimens of two complex phase steels. The residual stresses obtained from each process simulation and the roughness measured on the cut surface are included in the model to account for the influence of these operations on the material fatigue strength. Furthermore, standard uniaxial tensile properties and S–N data resulting from fatigue tests on as-polished specimens are the only material information required. A good agreement is found between the numerical fatigue life predictions and the experimental measurements, remaining below an error factor of three for all the estimated cases. In addition to coupon specimens, the model is also readily extensible to component-level applications, enabling the fatigue assessment of metallic engineering structures featuring shear-cut surfaces.This work has been done within the framework of the Fatigue4Light (H2020-LC-GV-06-2020) project: ‘‘Fatigue modeling and fast testing methodologies to optimize part design and to boost lightweight materials deployment in chassis parts’’. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 101006844. It has also been supported through the FatSAM project funded by the European Union’s Horizon Europe research and innovation program under grant agreement No 101159809. The authors Lucia Gratiela Barbu and Alejandro Cornejo are Serra Húnter Fellows. The authors gratefully acknowledge all the received support.Peer ReviewedPostprint (published version
Experimental characterisation and numerical modelling of a structured thermocline energy storage system under different operating conditions
No full textThis paper presents the first pilot-scale experimental demonstration of a molten salt structured thermocline thermal energy storage system. The study combines both experimental and numerical approaches to assess the performance and feasibility of this novel configuration. The experimental campaign was conducted at the thermal energy storage in molten salts (TESIS) facility at the DLR, where the storage tank consists of three vertically stacked baskets filled with clinker bricks. A series of dynamic cycling tests were carried out to evaluate the system's response under realistic operating conditions. In parallel, an unsteady and one-dimensional model was developed to simulate the thermal behaviour of the structured thermocline consisting of different layers of material. The model was validated against experimental data, showing good agreement across various charging and discharging cycles with different cutoff temperatures and mass flow rates. The experiments showed that allowed cut-off temperature affected the thermocline thickness much more than the mass flow rate. Moreover, the experiments successfully demonstrated the feasibility of the thermocline storage concept with refractory bricks, as it was possible to establish a stable thermocline for multiple cycles, confirming the potential of structured configurations for large-scale thermal storage applications.This work is carried out in the framework of the Newcline project. It is supported under the umbrella of CSP-ERA.NET 1st Cofund Joint Call and by the following National Agencies: AEI (Spain), CDTI (Spain), Jülich (Germany), and SFOE (Switzerland). CSP-ERA.NET is supported by the European Commission within the EU Framework Programme for Research and Innovation Horizon 2020 (Cofund ERA-NET Action, N ◦ 838311). Oriol Sanmartí acknowledges the financial support from the “Departament de Recerca i Universitats de la Generalitat de Catalunya” and the “Fons Social Europeu” with the predoctoral grant JOAN OR´ O FI AGAUR (2023 FI 00192).Peer ReviewedPostprint (published version
Radio wave propagation through a characterized CO2 plasma flow
No full textThe high levels of ionization of the plasma layer created around a spacecraft during the reentry in planetary atmospheres can cause disruption of the communications, leading to a radio blackout phenomenon. The entry, descending and landing phase of a Mars mission includes degradation and complete loss of the signal for a few minutes. This work, as part of the Horizon 2020 Magnetohydrodynamics Enhanced Entry System for Space Transportation (MEESST) project, presents experimental measurements of radio signal propagation for the first time through a stagnant flow of a CO2 plasma, representative of Mars entry flows. The measurements are conducted at the VKI plasma wind tunnel, the Plasmatron facility, using conical horn antennas at the Ka-band, transmitting inside an optimally designed probe. The probe designed at VKI and its characterization at the UPC anechoic chamber are detailed. The temperature of the plasma flow is measured by means of optical emission spectroscopy, to estimate the plasma frequency and to correlate it with the experimental signal propagation results. The measurements at the plasma wind tunnel show that the signal propagates almost undisturbed for low electric powers (and plasma frequencies), being its magnitude attenuated and its polarization rotated at higher electric powers, when the electron number densities are higher.Diana Luís research is funded by a doctoral fellowship (2021.04930.BD) granted by Fundação para a Ciência e Tecnologia (FCT Portugal). The MEESST project is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 899298. Prof. Adriano Camps research is funded by project GENESIS (PID 2021-126436OB-C21) sponsored by MCIN/AEI/10.13039/5011000H033/ and EU ERDF “A way to do Europe!”.Peer ReviewedPostprint (published version
Transparent solar cells based on a-Si1-xCx:H alloys: from silicon to carbon-rich absorbers
No full textAmorphous silicon-based absorbers have re-emerged in recent years as a good choice for implementing highly reliable transparent photovoltaic devices. While this technology ensures long-term stability and scalability, amorphous silicon exhibits relatively high absorption in the ultraviolet and visible part of the spectrum. This work reports on the use of hydrogenated amorphous silicon-carbon (a-Si1-xCx:H) films as a transparent absorber. By varying the carbon content, the properties of the absorber can be tuned, resulting in transparent devices with average photopic transmittance greater than 60% and a light utilization efficiency of approximately 1.3%. Additionally, the introduction of carbon enhances solar cell performance under low light irradiance, which is a typical condition in indoor photovoltaic applications.Postprint (published version
Integrating electrical conductivity capability into 3D printed alginate-gelatin hydrogels as skin tissue constructs for temperature sensing
No full textThe development of electrically conductive hydrogels has emerged as a critical advancement in soft electronics, enabling multifunctional devices for biomedical applications. This work introduces biocompatible and conductive three-dimensional (3D) printed hydrogels based on alginate-gelatin matrices, modified with gold nanoparticles (AuNPs) and MXene nanosheets (Ti3C2T¿), as electronic-engineered skin hybrid platforms for temperature sensing. The hydrogels demonstrate tunable conductivity, reaching values of 0.44¿S/m for AuNP-modified and 1.04¿S/m for MXene-modified samples. Structural analysis confirmed the preservation of a porous architecture, while rheological studies highlighted their mechanical integrity. Both modifications imparted temperature sensitivity, with an approximately 20¿% increase in current response between 30¿°C and 40¿°C and sensitivities in the range from -1.54–2.00 %ºC-1. These hydrogels also exhibit excellent cytocompatibility, making them ideal candidates for engineered skin scaffolds. The combination of temperature sensing and biocompatibility advances the potential use of conductive hydrogels in real-time physiological monitoring and infection detection, marking a significant contribution to the field of bioelectronics.Authors acknowledge funding from MCIU/AEI /10.13039/501100011033 / FEDER, UE (PLEC2022–009279, CNS2022–136109, PID2021–125767OB-I00, PID2022–137962OB-I00, and PID2022–141120OB-I00) and Agència de Gestió d′Ajuts Universitaris i de Recerca de Catalunya (AGAUR) (2021 SGR 01368, 2021 SGR 00387) for financial support. J.G.-T. acknowledges the Serra Hunter program of the Generalitat de Catalunya. M.P.G. and C.A. received support for the research from the Generalitat de Catalunya through the prize “ICREA Academia”. This work is also part of Maria de Maeztu Units of Excellence ProgrammeCEX2023–001300-M funded by MCIN/AEI/10.13039/501100011033.Peer ReviewedPostprint (published version
Short-time variational mode decomposition
No full textVariational mode decomposition (VMD) and its extensions like Multivariate VMD (MVMD) decompose signals into ensembles of band-limited modes with narrow central frequencies using Fourier transformations. However, since these transformations span the entire time-domain signal, they are suboptimal for analyzing non-stationary time series. We introduce Short-Time Variational Mode Decomposition (STVMD), an innovative extension of VMD that incorporates Short-Time Fourier transform (STFT) to minimize the impact of local disturbances. STVMD segments signals into short time windows and converts these segments into the frequency domain. It then formulates a variational optimization problem to extract band-limited modes representing the windowed data. The optimization aims to minimize the sum of mode bandwidths across the windowed data, extending the cost functions used in VMD and MVMD. Solutions are derived using the alternating direction method of multipliers, ensuring extraction of modes with narrow bandwidths. STVMD is divided into dynamic and non-dynamic types, depending on whether central frequencies vary with time. Our experiments show non-dynamic STVMD matches VMD with properly sized time windows, while dynamic STVMD better accommodates non-stationary signals through reduced mode function errors and tracking of dynamic frequencies. This effectiveness is validated using steady-state visual-evoked potentials in electroencephalogram signals.This work was supported by the National Key R&D Program of China (No. 2025YFE0107700), the Tianjin Science and Technology Plan Project (No. 24ZXYXSY00140).Peer ReviewedPostprint (published version
Step-wise current reactive flash sintering of Ba0.85Ca0.15Ti0.90Zr0.10O3 (BCZT) ceramics: structure and electrical properties
No full textThis study presents the first demonstration of the preparation of the lead-free piezoelectric ceramic Ba0.85Ca0.15Ti0.90Zr0.10O3 (BCZT) by reactive flash sintering (RFS). It is shown that by using step-wise current controlled ramps, it is possible to obtain homogeneous and phase-pure specimens at reduced furnace temperature (1100ºC) in 10¿min. Thus, RFS allows synthesis and sintering to be performed in a single step, resulting in significant energy and time savings compared to conventional processes such as solid-state reaction, which typically require multiple stages such as calcination followed by sintering for long periods of time at temperatures typically higher than 1300ºC. The effect of the synthetic atmosphere on the final structural, microstructural, ferroelectric and piezoelectric properties of the obtained ceramics is evaluated by the simultaneous use of several characterization techniques. It is shown that structurally and microstructurally the tunable atmosphere has no noticeable effect, whereas significant differences were found in terms of ferroelectric and piezoelectric properties.This work has been supported by funds from Spanish Ministry of Science and Innovation (PID2022-140815OB-C22 and PID2022-141199OA-I00), which are acknowledged.Peer ReviewedPostprint (published version
A real-time speech interaction analytics framework for group activities using SNA and LLM techniques
No full textIn the current digital era, analyzing the dynamics of interaction in groups presents challenges in fields such as education, the business sector, and healthcare. The lack of integrated tools that monitor and evaluate discursive and social interactions in real-time makes it difficult to understand the flow of collaboration, the formation of effective teams, or the monitoring of social cognitive processes. In this article, we present a framework designed to analyze speech interactions in group activities by combining Social Network Analysis (SNA) and Large Language Models (LLM). Naira enables the real-time capture, processing, and analysis of speech interaction data, providing tools to evaluate discursive effectiveness and collaborative dynamics. The framework’s components are detailed in its different stages, and application cases are explored in educational, business, and healthcare contexts. A proof of concept in an educational environment proves the versatility and potential of the proposal to improve the understanding and optimization of group processes. Integrating SNA and LLM offers a comprehensive perspective combining validated and interpretable techniques to analyze attribute and relational variables with advanced and current artificial intelligence techniques. The framework’s main innovation lies in its ability to fuse the quantitative structural analysis of SNA with the semantic and qualitative content analysis of LLMs, offering a novel perspective that overcomes the limitations of each technique in isolation.This work was partially funded by Escuela de Ingeniería Informática, Universidad de Valparaíso, Chile, through the REXE grant No. 4054/2022. Diego Monsalves was partially funded by the National Doctoral Scholarship ANID Chile, exempt resolution 4402/2023. H. Cornide-Reyes has been supported by DIUDA (Dirección de Investigación de la Universidad de Atacama) Regular Project of the Universidad de Atacama, No. 22386.Peer Reviewed9 - Indústria, Innovació i Infraestructura9.4 - Per a 2030, modernitzar les infraestructures i reconvertir les indústries perquè siguin sostenibles, usant els recursos amb més eficàcia i promovent l’adopció de tecnologies i processos industrials nets i racionals ambientalment, i aconseguint que tots els països adoptin mesures d’acord amb les capacitats respectives9.5 - Augmentar la investigació científica i millorar la capacitat tecnològica dels sectors industrials de tots els països, en particular els països en desenvolupament, entre d’altres maneres fomentant la innovació i augmentant substancialment, d’aquí al 2030, el nombre de persones que treballen en el camp de la investigació i el desenvolupament per cada milió d’habitants, així com la despesa en investigació i desenvolupament dels sectors públic i privatPostprint (author's final draft
Development and characterization of bioplastics based on different varieties of corn starch (Zea mays L.): Morphological, thermal and mechanical properties
No full textIn response to the growing demand for sustainable packaging alternatives, this study aimed to develop and characterize edible, biodegradable biofilms produced from starches extracted from five corn varieties (Zea mays L.): yellow, white, colorado, purple-husk, and purple. The starches from the varieties were evaluated for extraction yield, amylose content, and presence of bioactive compounds, while the resulting biofilms were characterized in terms of morphological, barrier, thermal, and mechanical properties. Starch extraction yield ranged from 18.31 % (yellow corn) to 30.40 % (white corn), with the latter showing highest efficiency. The average amylose content was 26.87 %, with purple corn presenting the highest value (27.80 ± 0.22 %) and purple-straw corn the lowest (25.90 ± 0.05 %). Bioactive compounds such as lutein, zeaxanthin, gallic acid, and cinnamic acid were identified in all varieties, with purple corn exhibiting the highest concentrations of lutein (2.53 µg/g) and zeaxanthin (10.14 µg/g). The films showed thickness between 0.056 and 0.060 mm and water solubility ranging from 27.08 ± 4.31 % (white corn, least soluble) to 37.22 ± 0.40 % (purple corn, most soluble), as well as significant color differences (¿E from 1.80 to 27.57). Thermal analysis revealed maximum gelatinization temperatures between 95 °C and 110 °C, while storage modulus (E') varied from 800 to 1400 MPa. These results highlight the potential of starches from different corn varieties, particularly purple corn, for developing functional bioplastics. The films exhibited suitable physical, thermal, and bioactive properties for use as edible coatings and biodegradable packaging, representing sustainable, value-added alternatives for the food industryMinisterio de Ciencia e Innovación, Spain Government (PROFOOD, CNS2023-144555). The author Farayde Matta Fakhouri are Serra Húnter Fellows of the Generalitat de CatalunyaPostprint (published version
A Non-intrusive data-driven approach towards a solution of the inverse problem of bending dielectric elastomer actuators
No full textDielectric Elastomer Actuators (DEAs), particularly bending DEAs, have gained significant attention due to their applications in soft robotics, biomimetic systems, and adaptive structures. Recent advancements in computational mechanics and the finite element method (FEM) have enabled accurate simulations of these actuators by incorporating their nonlinear mechanical behavior at large deformations and the coupling between mechanical and electrical responses. However, DEA design often involves solving inverse problems, which become computationally expensive when relying solely on direct simulations. To mitigate this cost, a fast surrogate model is needed. This study proposes a Reduced Order Model (ROM)-based methodology to efficiently determine the optimal locations and magnitudes of applied external potentials in a bending DEA to achieve a desired displacement response. The approach leverages nonlinear dimensionality reduction techniques, specifically Kernel Principal Component Analysis (kPCA) and Isometric Mapping (Isomap), to construct a surrogate model that accurately predicts DEA displacement responses from existing data without modifying the underlying FEM formulation. Using this surrogate model, the inverse problem is solved efficiently, achieving high accuracy (<2 % error) while significantly reducing computational cost. The methodology is validated on two different bending DEA geometries, demonstrating its effectiveness in both surrogate modeling and time-efficient inverse problem solving.The group acknowledge the financial support received via project POTENTIAL (PID2022-141957OB-C21) funded by MI-CIU/AEI/10.13039/501100011033/FEDER, UE. The first author also acknowledges the funding PREP2022-000220 provided by MICIU/AEI/10.13039/501100011033 and the FSE+.Peer ReviewedPostprint (published version