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Climate change heterogeneity: A new quantitative approach
Get PDFClimate change is a spatial and temporarily non-uniform phenomenon that requires understanding its evolution to better evaluate its potential societal and economic impact. The value added of this paper lies in introducing a quantitative methodology grounded in the trend analysis of temperature distribution quantiles to analyze climate change heterogeneity (CCH). By converting these quantiles into time series objects, the methodology empowers the definition and measurement of various relevant concepts in climate change analysis (warming, warming typology, warming amplification and warming acceleration) in a straightforward and robust testable linear regression format. It also facilitates the introduction of new testable concepts like warming dominance to compare (globally or partially) the warming process experienced by different regions. Furthermore, the methodology holds the added significance of concurrently encompassing both temporal and spatial dimensions in temperature analysis, owing to the close alignment between unconditional quantiles and latitude measures. Applying our quantitative methodology for the period 1950-2019 to the Globe (2192 stations) and Spain (30 stations) as a benchmark region, we find that both experience a distributional warming process (beyond the standard average) but of very different types. While the Globe experiences a stronger warming in the lower temperatures than in the upper ones, Spain evolves from equal warming in the whole distribution toward a stronger warming in the upper quantiles (similar to the warming process experienced in the African continent). In the two cases, the warming process accelerates (non-linear behavior) over time and is asymmetrically amplified. Overall, although both the Globe and Spain suffer an equivalent warming process in the median (mean) temperature, Spain's warming dominates the Globe in the upper quantiles and is dominated in the lower tail of the global temperature distribution that corresponds to the Arctic region. Our climate change heterogeneity results open the door to the need for a non-uniform causal-effect climate analysis that goes beyond the standard causality in mean and for a more efficient design of the mitigation-adaptation policies. In particular, the heterogeneity found suggests these policies should contain a common global component and a clear local-regional idiosyncratic element. The latter is usually more straightforward to implement
Fully convolutional networks for velocity-field predictions based on the wall heat flux in turbulent boundary layers
Get PDFFully-convolutional neural networks (FCN) were proven to be effective for predicting the instanta-neous state of a fully-developed turbulent flow at different wall-normal locations using quantities measured at the wall. In Guastoni et al. (J Fluid Mech 928:A27, 2021. https://doi.org/10.1017/jfm.2021.812), we focused on wall-shear-stress distributions as input, which are difficult to measure in experiments. In order to overcome this limitation, we introduce a model that can take as input the heat-flux field at the wall from a passive scalar. Four different Prandtl numbers Pr = ν/α = (1, 2, 4, 6) are considered (where ν is the kinematic viscosity and α is the thermal diffusivity of the scalar quantity). A turbulent boundary layer is simulated since accurate heat-flux measurements can be performed in experimental settings: first we train the network on aptly-modified DNS data and then we fine-tune it on the experimental data. Finally, we test our network on experimental data sampled in a water tunnel. These predictions represent the first application of transfer learning on experimental data of neural networks trained on simulations. This paves the way for the implementation of a non-intrusive sensing approach for the flow in practical applications.Open access funding provided by Royal Institute of Technology. This work is supported by the founding provided by the Swedish e-Science Research Centre (SeRC), ERC grant no. “2021-CoG-101043998, DEEPCONTROL” and the Knut and Alice Wallenberg (KAW) Foundation. S.D., A.I. and F.F. acknowledge funding by the project ARTURO, ref. PID2019-109717RB-I00/AEI/10.13039/501100011033, funded by the Spanish State Research Agency and the project EXCALIBUR (Grant No PID2022-138314NB-I00), funded by MCIU/AEI/10.13039/501100011033 and by ‘ERDF A way of making Europe’
Deep learning-based segmentation of head and neck organs at risk on CBCT images with dosimetric assessment for radiotherapy
Get PDFObjective. Cone beam computed tomography (CBCT) has become an essential tool in head and neck cancer (HNC) radiotherapy (RT) treatment delivery. Automatic segmentation of the organs at risk (OARs) on CBCT can trigger and accelerate treatment replanning but is still a challenge due to the poor soft tissue contrast, artifacts, and limited field-of-view of these images, alongside the lack of large, annotated datasets to train deep learning (DL) models. This study aims to develop a comprehensive framework to segment 25 HN OARs on CBCT to facilitate treatment replanning. Approach. The proposed framework was developed in three steps: (i) refining an in-house framework to segment 25 OARs on CT; (ii) training a DL model to segment the same OARs on synthetic CT (sCT) images derived from CBCT using contours propagated from CT as ground truth, integrating high-contrast information from CT and texture features of sCT; and (iii) validating the clinical relevance of sCT segmentations through a dosimetric analysis on an external cohort. Main results. Most OARs achieved a dice score coefficient over 70%, with mean average surface distances of 1.30 mm for CT and 1.27 mm for sCT. The dosimetric analysis demonstrated a strong agreement in the mean dose and D2 (%) values, with most OARs showing non-significant differences between automatic CT and sCT segmentations. Significance. These results support the feasibility and clinical relevance of using DL models for OAR segmentation on both CT and CBCT for HNC RT.Research supported by Projects AC20/00102 (Ministerio de Ciencia, Innovación y Universidades, Instituto de Salud Carlos III, Asociación Espanola Contra el Cáncer and European Regional Development Fund ''Una manera de hacer Europa''), project PerPlanRT (under the frame of ERA PerMed), TED2021-129392B-I00, TED2021-132200B-I00, PID2023-149604OB-I00 (European Union Next Generation EU/PRTR and MCIN/AEI/10.13039/501 100 011 033)
In-silico platform for the multifunctional design of 3D printed conductive components
No full textThe effective electric resistivity of conductive thermoplastics manufactured by filament extrusion methods is determined by both the material constituents and the printing parameters. The former determines the multifunctional nature of the composite, whereas the latter dictates the mesostructural characteristics such as filament adhesion and void distribution. This work provides a multi-scale computational framework to evaluate the thermo-electro-mechanical behaviour of printed conductive polymers. A full-field homogenisation model first provides the influence of material and mesostructural features (i.e., filament orientations, voids and adhesion between filaments). Then, a macroscopic continuum model elucidates the effects of thermo-electro-mechanical mixed boundary conditions. The in-silico multi-scale methodology is validated with extensive original multi-physical experiments and a functional application consisting of an electro-heatable printing cartridge. Overall, this work establishes the foundations to virtually break the gap between mesoscopic and macroscopic multifunctional responses in conductive components manufactured by additive manufacturing techniques.The authors acknowledge Prof. Marc-Andre Keip for his advice in relation with the numerical formulation. JCM, SGH and DGG acknowledge support from the 2024 Leonardo Grant LEO24-1-12283-ING-ING-13 for Scientific Research and Cultural Creation from the BBVA Foundation. The BBVA Foundation accepts no responsibility for the opinions, statements and contents included in the project and/or the results thereof, which are entirely the responsibility of the authors. The authors acknowledge support from MCIN/AEI/10.13039/501100011033 under Grant number TED2021-129709B-I00, and from the European Union NextGenerationEU/ PRTR. SGH acknowledges support from the Talent Attraction grant (CM 2022 - 2022-T1/IND-23971) from the Comunidad de Madrid, Spain. EMP acknowledges financial support from UKRI’s Future Leaders Fellowship programme [grant MR/V024124/1]
LiDAR-based perception system for logistics in industrial environments
No full textAutonomous vehicles in logistics and industrial environments demand robust and efficient perception systems. This study presents a LiDAR-based perception system designed for such environments, focusing on real-time deterministic obstacle detection and tracking with limited computational power. The proposed multi-stage approach leverages 3D data from LiDAR sensors. First, ground removal is performed to filter out static ground points. Then, a filtering step is applied using precomputed maps of the navigation area to filter out static zones from the LiDAR point clouds. After, object segmentation distinguishes structural elements from potential obstacles, followed by clustering and Principal Component Analysis (PCA) to accurately estimate obstacle pose and volume. An obstacle-tracking method ensures continuous monitoring over time. Extensive experiments in realistic logistics and industrial scenarios have been performed, comparing the proposed approach to state-of-the-art deep-learning-based methods, demonstrating the system¿s high performance in both accuracy and efficiency.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work has been partially funded by the Industrial Technology Development Center (CDTI in Spanish) and supported by the Spanish Science and Innovation Ministry through the project R3CAV (ref. PTAS-20211009). Furthermore, this research has been supported by the Spanish Government through projects PID2021-128327OA-I00 and TED2021-129374A-I00 funded by MCIN/AEI /10.13039/501100011033 and by the European Union NextGenerationEU/PRTR. Funding for APC: Universidad Carlos III de Madrid (Agreement CRUE-Madroño 2025)
Towards Goal-Oriented Semantic Orchestration for Resource-Aware Robotic Function Offloading
No full textEdge computing is increasingly seen as the perfect enabler for distributed robotic applications requiring low latency and high adaptability. However, current approaches offload computational tasks exclusively to edge nodes, overlooking scenarios where onboard processing can meet performance targets. Therefore, we propose a framework that unifies offloading decision and resource orchestration into a single algorithm that compares different allocation strategies under accuracy, latency, and energy goals. Results show that this approach admits more functions while maintaining strict performance targets, offering substantial gains in overall system utilityThis work was partially funded by the EC through the SNS JU PREDICT-6G project under grant agreement No.101095890; 6GINSPIRE PID2022-137329OB-C42, funded by MCIN/AEI/10.13039/501100011033, and project UNICO 5G I+D 6G-EDGEDT
Compact Bistatic Iterative Passive Radar Based on Terrestrial Digital Video Broadcasting Signals
No full textPassive radar has become very popular in recent years because it is usually undetectable, and countermeasures used to prevent its functioning are complex and, in general, easily identified. Terrestrial digital video broadcasting (DVB-T) is commonly used as an opportunistic illumination signal because of its large range and widespread deployment, both of which make it applicable to almost all scenarios. This paper presents the design of a compact and robust receiver for passive radar that uses a low number of antenna while achieving high accuracy. In order to do this, we use an iterative algorithm to refine the initial estimations based on time-domain channel information to converge to the true estimations. This is especially effective when the signal-to-noise-ratio (SNR) at the receiver is moderate and/or there are several reflections in the environment that may introduce some error into schemes that perform the angle of arrival or time of arrival for the estimation. The algorithm proposed herein is able to accurately estimate the position of a target with a low SNR.This work was partly funded by Project SOFIA-AIR (PID2023-147305OB-C31) (MICIU /10.13039/501100011033/AEI/EFDR, UE)
High-velocity fragmentation of titanium alloy rings and cylinders produced using Field-Assisted Sintering Technology
No full textThis paper explores the mechanics of high-velocity impact fragmentation in titanium alloys pro-duced by Field-Assisted Sintering Technology. For that purpose, we have utilized the experimental setups recently developed by Nieto-Fuentes et al. (J Mech Phys Solids 174:105248, 2023a; Int J Impact Eng 180:104556, 2023b) for conducting dynamic expan-sion tests on rings and cylinders. The experiments involve firing a conical-nosed cylindrical projectile using a single-stage ight-gas gun against the stationary ring/cylinder at velocities ranging from ≈ 248 m/sto≈ 390 m/s, corresponding to estimated strain rates in the specimen varying from ≈ 10050 s−1 to ≈ 19125 s−1. The diameter of the cylindrical part of the projec-tile exceeds the inner diameter of the ring/cylinder, causing the latter to expand as the projectile moves forward, resulting in the formation of multiple necks and fragments. Two different alloys have been tested: Ti6Al4V and Ti5Al5V5Mo3Cr. These materials are widely utilized in aeronautical and aerospace industries for constructing structural elements such as compres-sor parts (discs and blades) and Whipple shields, which are frequently exposed to intense mechanical loading, including high-velocity impacts. However, despite the scientific and technological significance of Ti6Al4V and Ti5Al5V5Mo3Cr, and the extensive research on their mechanical and fracture behaviors, to the best of the authors’ knowledge, no systematic study has been conducted thus far on the dynamic fragmentation behavior of these alloys. Hence, this paper presents an ambitious fragmentation testing program, encom-passing a total of 27 and 29 experiments on rings and cylinders, respectively. Monolithic and multimaterial samples—half specimen of Ti6Al4V and half specimen of Ti5Al5V5Mo3Cr—have been tested, taking advan-tage of the ability of Field-Assisted Sintering Technol-ogy to produce multimaterial parts. The fragments have been collected, weighed, sized, and analyzed using scanning electron microscopy. The experiments have shown that the number of necks, the number of frag-ments, and the proportion of necks developing into fragments generally increase with expansion velocity. The average distance between necks has been assessed against the predictions of a linear stability analysis (Zhou et al. in Int J Impact Eng 33:880–891 2006; Vaz-Romero et al. in Int J Solids Struct 125:232–243, 2017), revealing satisfactory agreement between the-oretical predictions and experimental results. In addi-tion, the experimental results have been compared with tests reported in the literature for various metals and alloys (Nieto-Fuentes et al. in J Mech Phys Solids 174:105248, 2023a; Zhang and Ravi-Chandar in Int J Fract 142:183–217, 2006, Zhang and Ravi-ChandarOpen Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. The research leading to these results has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme. Project PURPOSE, grant agreement 758056. J. C. Nieto-Fuentes acknowledges support from the CONEX-Plus programme funded by Universidad Carlos III de Madrid and the European Union’s Horizon 2020 research and innovation programme, under the Marie Skłodowska-Curie grant agreement 801538. This work was supported through the Engineering and Physical Sciences Research Council (EPSRC), grant EP/T024992/1 Doing More With Less. The EPSRC for funding equipment in the Henry Royce Institute at Sheffield, grant numbers EP/R00661X/1 and EP/P02470X/1, is gratefully acknowledged
A Multibody-Based Benchmarking Framework for the Control of the Furuta Pendulum
No full textThe Furuta pendulum is a well-known benchmark in the field of underactuated mechanical systems due to its reduced number of control inputs compared to its degrees of freedom, and richly nonlinear behavior. This work addresses the challenge of accurately modeling and controlling such a system without relying on traditional linearization techniques. In contrast to the common approach based on Lagrangian analytical modeling and state¿pace linearization, we propose a methodology that integrates a high-fidelity multibody model developed in Simscape Multibody (MATLAB), capturing the complete nonlinear dynamics of the system. The multibody model includes all geometric, inertial, and joint parameters of the physical hardware and interfaces directly with Simulink, enabling realistic simulation and control integration. To validate the physical fidelity of the multibody model, we perform a frequency-domain analysis of the pendulum's natural free response. The dominant vibration frequency extracted from the simulation is compared with the theoretical prediction, demonstrating accurate capture of the system's inertial and dynamic properties. This validation strategy strengthens the reliability of the model as a digital twin. The classical analytical formulation is provided to validate the simulation model and serve as a comparative framework. This dual modeling strategy allows for benchmarking control strategies against a trustworthy nonlinear digital twin of the Furuta pendulum. Preliminary experimental results using a physical prototype validate the feasibility of the proposed approach and set the foundation for future work in advanced nonlinear control design using the multibody representation as a digital validation tool.This research was funded by the Spanish Government’s Ministry of Science and Innovation Grant Number PID2020-116984RB-C21-C22
Effect of heating and neutron irradiation on the FTIR dating
No full textThis research was carried out as part of a doctoral thesis directed by Dr. Elisa Ruiz of the University Carlos III of MadridIn this work, we provide an analysis of the Fourier Transform InfraRed (FTIR) spectra of several modern linen samples that had been irradiated with neutrons. A nondestructive dating method based on this FTIR spectroscopy was developed for archaeological linen textiles. Its uncertainty is considerably greater than the usual radiocarbon dating (C14). However, rare effects such as neutron irradiation could modify the C14 dating and make it not applicable. FTIR, although it is not a competitive dating method, could exclude or confirm those uncommon events and therefore the applicability of the C14 dating. To explore this utility, we analyze whether the FTIR dating method would still be applicable in a neutron irradiation event. On the other hand, the effects of heating on the FTIR dating must also be analyzed. Among other cases, this study could apply to the case of the Shroud of Turin. Furthermore, we propose a nondestructive FTIR test to elucidate whether or not this purported relic received a neutron irradiation.Funding for APC: Universidad Carlos III de Madrid (Agreement CRUE-Madroño 2024)