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Impact of different descriptions for diffusion, heat transfer, and capillary pressure on a physics-based proton-exchange membrane fuel cell model

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International Journal of Hydrogen Energy 2025年 133卷 386-401页

作者： Carneiro, Leonardo F. Costa Junior, Esly F. de P. Andrade, Samuel T. Matencio, Tulio Postgraduate Program in Chemical Engineering PPGEQ-UFMG Brazil Postgraduate Program in Mechanical Engineering PPGMEC-UFMG Brazil Department of Chemistry DEQ/ICEX-UFMG UFMG Brazil

A physics-based, two-phase, and non-isothermal proton-exchange membrane fuel cell model is developed and used to evaluate the impact of three common modeling assumptions concerning mass and heat transport in a single-cell system. Firstly, using Fick's law to describe the diffusive transport caused significant differences in the concentration profiles when compared to the Stefan-Maxwell equation, resulting in considerable deviations in the polarization curve. Moreover, the description of thermal effects is found to be crucial to obtaining accurate water molar fraction profiles for the cathode, even when heat removal is effective. Finally, while the impact related to the capillary pressure description in the polarization curve is insignificant when ohmic losses dominate, as they considerably affect the liquid water and oxygen profiles, they may be crucial to obtain precise values at high current densities when water removal is less efficient. These results should provide valuable insights for the development of better models. © 2025 Hydrogen Energy Publications LLC

关键词： Maxwell equations

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A Systematic Evaluation of Clustering Algorithms Against Expert-Derived Clustering

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Operations Research Forum 2025年第2期6卷 1-24页

作者： Mikrou, Ioannis Sapidis, Nickolas S. Department of Mechanical Engineering University of Western Macedonia ZEP Kozani 50100 Greece Postgraduate Masters Program “Quality Management and Technology” Hellenic Open University Par. Aristotelous 18 Patras 26335 Greece

Clustering algorithms have long sought to replicate human expertise in data clustering. This research utilizes six mechatronic products and a team of domain experts to assess how closely the results of six clustering algorithms align with expert-generated outcomes. This comparison of clustering results includes validation indices, the analysis of component migrations between the generated clusters, and optical inspection. The mechatronic products were selected for their complex nature, which provides a challenging context for the clustering analysis. The algorithms used in this research are Ward’s method (WARD), partitioning around medoids (PAM), K-means (K-MEANS), divisive analysis (DIANA), density-based spatial clustering of applications with noise (DBSCAN), and clustering by fast search and find of density peaks (DPC), and the validation indices employed to evaluate the clustering results are the silhouette coefficient (SC) and the composed density between and within clusters (CDbw). © The Author(s) 2025.

关键词： Clustering performance DSM models Human expert benchmarks Machine learning Mechatronics

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Self SOC Estimation for Second-Life Lithium-Ion Batteries

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IEEE Access 2025年 13卷 75033-75042页

作者： Gotz, Joelton Deonei Viana, Emilson Ribeiro Galvão, José Rodolfo Corrêa, Fernanda Cristina Borsato, Milton Badin, Alceu André Paraná Curitiba81280-340 Brazil Department of Computer Science Paraná Curitiba80215-901 Brazil Department of Physics Paraná Curitiba81280-340 Brazil Paraná Ponta Grossa80230-901 Brazil Postgraduate Program in Mechanical and Materials Engineering Paraná Curitiba81280-340 Brazil

Lithium-ion batteries (LIB) are the mainstream technology for energy storage in several industrial segments, such as mobility and stationary systems for solar, wind, or other alternative energy source. This technology has a long lifetime, low self-discharge, high capacity and density, and can store energy longer. Despite that, LIB is suitable to supply power for electric mobility if its state of health (SOH) is higher than 80%. Then, an alternative for batteries with SOH below that is recycling or second-life batteries (SLB). The first is expensive and complex;only some companies retain the technology. Still, the SLB can be an excellent solution to maintaining LIBs in operation for slow vehicles or stationary systems. However, SLB requires intelligent battery management systems (BMS) because the packs are composed of cells with different characteristics, which makes the operation more difficult. This work presents a system consisting of two Machine Learning (ML) layers to automatically estimate the state of charge (SOC) of SLB independent of the battery’s capacity or age. In the first phase, a Random Forest (RF) model was built and trained to discover the curve capacity of different SLB characteristics and capacities. After the capacity curve selection, in the second phase, a new RF model was built and trained for each capacity curve to make SOC inferences of the batteries. The discharge data curve of one hundred batteries was used for the development, whereas eighteen were used for the training and eighty-two for tests. The results indicated a root square mean error (RSME) below 45 mAh for the capacity estimation (phase 1), and an RSME below 0.87% was found in the second phase for the SOC estimation. Finally, the capacity and SOC models have been inserted in a Raspberry system to measure the main parameters of SLB (voltage and current) and make inferences in real time independent of the cell’s age. The results showed an RSME below 100 mAh for the first layer and be

关键词： Lithium-ion batteries

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ANN-based analysis of thin film Maxwell fluid dynamics with electro-osmotic and nonlinear thermal effects

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Alexandria engineering Journal 2025年 127卷 392-410页

作者： Din, Irfan Saif Ud Siddique, Imran Zahid, Zohaib Nadeem, Muhammad Islam, S. Department of Mathematics University of Management and Technology Lahore54770 Pakistan Department of Mathematics University of Sargodha Sargodha40100 Pakistan Mathematics in Applied Sciences and Engineering Research Group Scientific Research Center Al-Ayen University Nasiriyah64001 Iraq Federal University of Technology Paran UTFPR Mechanical Engineering Department DAMEC Postgraduate Program in Mechanical and Materials Engineering PPGEM Research Center for Rheology and Non-Newtonian Fluids CERNN R. Deputado Heitor Alencar Furtado 5000 - Bloco N - Ecoville PR Curitiba81280-340 Brazil Department of Mechanical Engineering Prince Mohammad Bin Fahd University P.O Box 1664 Al Khobar31952 Saudi Arabia

An intelligent Levenberg-Marquardt Technique (LMT) with artificial neural network (ANN) backpropagation (BP) has been used to analyze the thermal heat and mass transfer of unsteady magnetohydrodynamics (MHD) thin film Maxwell fluid flow in a porous inclined sheet with an emphasis on the influence of electro-osmosis. The activation energy, chemical reaction, mixed convection, melting heat, joule heating, nonlinear thermal radiation, variable thermal conductivity and thermal source/sink effect are taken into account for transport expressions. Appropriate similarity transformations were used to translate partial differential equations (PDEs) into ordinary differential equations (ODEs). After that, the built-in MATLAB BVP4C method was used for a data set assessed using the LMT-ANN strategy to solve these ODEs. The physical significance of the designed parameters is thoroughly discussed in both tabular and graphical form. The observed R-squared value is 1, and the mean square error up to 10−15 demonstrates the LMT-ANN's precise and accurate computing capability. The model's validity is also confirmed by the strong agreement between the obtained predicted findings and numerical results, which shows a high degree of accuracy within the range of 10−8 to 10−11. It was revealed that radiative heat considerably increases surface heat energy through accumulation, improving heat transfer qualities, whereas fluid temperature is raised by Joule dissipation, variable thermal conductivity, and heat source. Electro-osmosis and magnetic fields reduce fluid velocity by generating opposing forces that resist the flow. This problem works best in microscale fluid transport systems and drilling operations, where magnetic and electro-osmotic control are crucial. These systems include micro-electromechanical systems, lab-on-a-chip devices, porous geological formations, and thin film coating technologies. © 2025 The Authors

关键词： Activation energy

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Wind speed forecasting approach using conformal prediction and feature importance selection

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International Journal of Electrical Power and Energy Systems 2025年 168卷

作者： Zuege, Cesar Vinicius Stefenon, Stefano Frizzo Yamaguchi, Cristina Keiko Mariani, Viviana Cocco Gonzalez, Gabriel Villarrubia Coelho, Leandro dos Santos Graduate Program in Electrical Engineering Federal University of Parana PR Curitiba Brazil Postgraduate Program in Productive Systems in Association with UNIPLAC UNC UNESC and UNIVILLE SC Brazil Department of Electrical Engineering Federal University of Parana PR Curitiba Brazil Graduate Program in Mechanical Engineering Federal University of Parana PR Curitiba Brazil Expert Systems and Applications Lab Faculty of Science University of Salamanca Salamanca37008 Spain

Wind energy is a rising renewable energy source that plays an important role in the transition to a more sustainable energy system. Variation in wind power generation is one of the main challenges facing this energy source. Wind forecasting approaches are essential for planning and operating wind farms, but are complex due to the dynamic nature of the wind and the influence of local factors. This paper evaluates short-term forecasting of time series with a measure of uncertainty associated with wind speeds. The proposed method considers the conformal prediction approach and, based on Shapley values, uses optimal selection of features given their importance. Furthermore, a Bayesian Optimization with Tree-structured Parzen Estimators (BO-TPE) will be used to tune the hyperparameters of the models. The results showed that using Variational Mode Decomposition (VMD) allied with Singular Spectrum Analysis (SSA) to feed into a conformal prediction model improved the performance of the model. Taking into account a Beutenberg data set, Germany, the best model was Light Gradient Boosting Machine (LGBM)-VMD-SSA without partial fit, resulting in a root mean squared error (RMSE) criterion of 0.25031, coverage measure of 94.4%, and width measure of 1.008. When considering a dataset from Limoeiro, Brazil, the best model was also LGBM-VMD-SSA without partial fit, resulting in an RMSE of 0.21597, a coverage of 90.3%, and a width of 0.678. SHapley Additive exPlanations (SHAP) bring explainability to the model results. The models proposed in this study, hypertuned by BO-TPE with interpretable results based on SHAP, can be useful in predicting wind speed and power generation. © 2025 The Authors

关键词： Windmill

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Production of cobalt- and manganese-based oxide nanofibers via solution blow spinning: Structural properties and high-performance oxygen evolution reaction

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Applied Surface Science 2025年 703卷

作者： Pereira, Thiago O. Raimundo, Rafael A. Alves, Ricardo F. Morales, Marco A. Simões, Thiago A. Medeiros, Eliton S. Macedo, Daniel A. Dutra, Ricardo P.S. Materials Science and Engineering Postgraduate Program Federal University of Paraíba PB João Pessoa58051-900 Brazil TEMA – Centre for Mechanical Technology and Automation Department of Mechanical Engineering University of Aveiro Aveiro3810-193 Portugal Department of Mechanical Engineering Federal University of Paraíba PB João Pessoa58051-900 Brazil Department of Theoretical and Experimental Physics Federal University of Rio Grande do Norte Natal59078-970 Brazil Cabo de Santo Agostinho PE 54518-430 Brazil Department of Materials Engineering Federal University of Paraíba PB João Pessoa58051-900 Brazil

Cobalt- and manganese-based oxides (Co3O4, MnCo2O4, and CoMn2O4) with nanofiber-like morphology were successfully synthesized via solution blow spinning (SBS) and evaluated as electrocatalysts for the oxygen evolution reaction (OER). The structural, morphological, and surface properties of the prepared materials were investigated through x-ray diffraction (XRD), field emission scanning electron microscope (FESEM), Fourier-transform infrared (FTIR), Raman spectroscopy, x-ray photoelectron spectra (XPS), and magnetic measurements. The magnetic characterization of MnCo2O4, CoMn2O4, and Co3O4 confirmed their phase purity and expected magnetic behavior. MnCo2O4 exhibited ferromagnetic ordering (θ = +145 K) with Hc = 8200 Oe and Ms = 11.9 emu/g at 5 K. CoMn2O4 showed multiple transitions at 178 K, 169 K, and 81 K, suggesting ferrimagnetic ordering. Co3O4 displayed antiferromagnetic behavior with a Néel temperature of 37 K. These results corroborate with the literature, validating the synthesis and characterization. X-ray photoelectron spectroscopy (XPS) analysis confirmed the oxidation states of Co and Mn and the presence of oxygen vacancies in CoMn2O4, MnCo2O4, and Co3O4. The Oads/Olats ratio indicated a higher concentration of oxygen vacancies in CoMn2O4 (1.21), while MnCo2O4 exhibited the highest Mn4+ content (Mn4+/Mn3+ = 0.76). The Co3+/Co2+ ratio was higher in MnCo2O4 (1.94), suggesting enhanced oxidation stability. The electrochemical characterization for OER in 1 M KOH electrolyte of the CoMn2O4, MnCo2O4, and Co3O4 samples displayed overpotentials of 330, 348, and 375 mV, respectively, to achieve a current density of 10 mA cm−2. Cyclic voltammetry and electrochemical impedance spectroscopy further corroborate these findings. The electrodes exhibited great stability maintaining their performance for 20 h. A detailed surface chemistry analysis showed that oxygen vacancy-rich samples exhibited enhanced charge transfer and generated Mn catalytic sites that facilitated

关键词： Fourier transform infrared spectroscopy

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Influence of submerged arc welding slag content variation on cementitious materials: A sustainable alternative

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Construction and Building Materials 2025年 483卷

作者： Castro-Lopes, S. Rodrigues, V.D. Marden, Sandro Peña-Garcia, R. Padrón-Hernández, E. Berenguer, Romildo Federal Institute of Education Science and Technology of Pará PA Altamira Brazil Laboratory of Composite Materials and Structural Integrity Corrosion and Biocorrosion - CompoLab/LBC Federal University of Pernambuco PE Recife Brazil Federal University of Paraiba Department of Mechanical Engineering PB Joao Pessoa Brazil Federal Rural University of Pernambuco Postgraduate Program in Physics Engineering Academic Unit of Cabo de Santo Agostinho Cabo de Santo PE Agostinho Brazil Federal University of Pernambuco Department of Physics PE Recife Brazil Polytechnic School University of Pernambuco PE Recife Brazil Federal University of Pernambuco Department of Mechanical Engineering PE Recife Brazil

This study evaluates the effects of submerged arc welding (SAW) slag as a partial replacement for Portland cement in cementitious materials. Cement pastes with 5 %, 10 %, 15 %, 20 %, 25 %, and 30 % SAW slag were tested for compressive strength, tensile strength, carbonation resistance, phase formation, and environmental impact. The results revealed that up to 10 % SAW slag significantly enhanced compressive strength, with the 5 % replacement showing a 20.10 % increase in strength at 28 days compared to the control. The mechanical improvement was attributed to the formation of the CSH phase, which was confirmed by X-ray diffraction (XRD) and thermogravimetric analysis (TGA). Carbonation tests indicated that the 5 % SAW samples reduced carbonation by 5 % compared to the control, while the 10 % SAW samples showed a 1 % reduction. This suggests that SAW slag enhances the resistance of cementitious materials to CO2 attack, improving long-term durability. XRD analysis also identified an increase in amorphous phases in the SAW samples, particularly in the 5 % addition, further supporting the pozzolanic activity of SAW slag. Pozzolanic effectiveness coefficient analysis revealed synergistic effects for SAW slag blends, with optimal performance observed at 5 % replacement, in line with microstructural evidence of enhanced CSH gel formation. Environmental analysis demonstrated that replacing 10 % of Portland cement with SAW slag could reduce CO2 emissions by approximately 4564 kg annually, while a 15 % replacement could lead to a reduction of 6846 kg of CO2. These results underscore the potential of SAW slag as a sustainable and performance-enhancing alternative to conventional cement in concrete production. © 2025 Elsevier Ltd

关键词： Compressive strength

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PRECIPITATION AND RECRYSTALLIZATION DURING PROCESSING OF A SUPERPLASTIC AL-10MG-0.1ZR ALLOY

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MATERIALS SCIENCE AND engineering A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING 1993年第1-2期166卷 135-143页

作者： MCNELLEY, TR CROOKS, R KALU, PN ROGERS, SA Materials Engineering Program Department of Mechanical Engineering Naval Postgraduate School Monterey CA 93943 USA

Microstructural evolution during thermomechanical processing (TMP) of a superplastic Al-10Mg-0.1Zr (weight per cent) alloy was studied. The TMP was carried out at 300-degrees-C and consisted of 12 rolling passes corresponding to a total strain of 2.5. Superplastic elongations at 300-degrees-C exceeded 1 000% for an optimum processing schedule involving a 30 min interpass anneal (IPA) time. Precipitation of the intermetallic beta-phase (Al8Mg5) was complete at an accumulated strain of 1.5 and the precipitate particle size and size distribution were found to be nearly constant for the remainder of the TMP. Particle stimulated nucleation (PSN) of recrystallization associated with prolonged IPA times accounted for the grain refinement necessary to support superplastic deformation. A model for PSN is applied to the data.

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Understanding the effect of preparation technique and compaction pressure on the microstructure, sinterability and mechanical properties of the Cu-20 wt% WC composite prepared with recycled WC

Journal of Alloys and Compounds Communications

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Journal of Alloys and Compounds Communications 2025年 6卷

作者： Rafael A. Raimundo Franciné A. Costa Marco A. Morales Daniel A. Macedo Angelus G.P. Silva Uílame U. Gomes Federal University of Paraíba Department of Materials Science and Engineering João Pessoa PB 58051-900 Brazil TEMA – Centre for Mechanical Technology and Automation Department of Mechanical Engineering University of Aveiro Aveiro 3810-193 Portugal Mechanical Engineering Postgraduate Program UFRN Natal 59078-970 Brazil Department of Theoretical and Experimental Physics UFRN Natal 59078-970 Brazil Materials Science and Engineering Postgraduate Program UENF Campos dos Goytacazes 28015-620 Brazil Materials Science and Engineering Postgraduate Program UFRN Natal 59078-970 Brazil

The study investigated the impact of different preparation techniques (mechanical Mixing - MM and High Energy Milling - HEM) and compaction pressures on the microstructure, sinterability and mechanical properties of the Cu-20 %WC composite using recycled WC. The results indicated that HEM promotes greater homogeneity, dispersion and refinement of the WC phase in copper, resulting in denser and more uniform microstructures after sintering. Although higher pressures increased the density of green compacts, they reduced densification during sintering, especially for powders prepared by MM, due to the segregation of the Cu and WC phases. On the other hand, compacts sintered with HEM powders prsented higher Vickers microhardness and better magnetic properties, attributed to the uniform distribution of WC particles and the increase in the interaction between the phases. Furthermore, the study highlights the influence of metallic impurities (Fe, Co and Ni) on the magnetic properties of the composite materials.

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Experimental evaluation of the emissions in an Otto cycle engine operating with hydrous and wet ethanol under different compression ratios 27

Experimental evaluation of the emissions in an Otto cycle en...

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27th SAE BRASIL International Mobility Technology Congress and Exhibition, BRASILCONG 2018

作者： Fagundez, Jean L. S. Sari, Rafael L. Martins, Mario E. S. Salau, Nina P. G. Chemical Engineering Postgraduate Program UFSM Mechanical Brazil

The ethanol fuel sold in Brazil, which is seen as an option that represents less polluting gases emitted into the atmosphere, goes through a period where its economic viability does not compensate its use against the alternative coming from nonrenewable sources. It is known that part of the cost associated with commercial ethanol is due to its purification through distillation, which decreases the water percentage in the final composition. Aiming to evaluate alternatives to reduce the final cost of the fuel, a comparison was made between the burning results of hydrous ethanol, with up to 5% of water by volume, and the wet ethanol, with 30% water by volume, in an Otto cycle engine, operating with a fixed speed of 1800 RPM and seeking the maximum brake torque in each test. Thus, these biofuels were tested in different compression ratios of 12.5: 1, 13.5: 1 and 14.5: 1, in order to evaluate the overall efficiency of the engine and the influence of this variable on the emissions of CO, NOx and unburned hydrocarbons. The results have shown that water increase in fuel composition, and consequent reduction of the combustion chamber temperature, led to a lost in indicated fuel conversion efficiency of wet ethanol when compared to commercial ethanol only in the lowest compression ratio, showing higher efficiency than the hydrous fuel in the other conditions. Meanwhile, volumetric efficiency shows a slight variation for the fuel with the higher percentage of water and combustion efficiency tends to improve with the increase in compression ratio. In addition, the lower temperature during combustion causes ethanol with 30% water by volume to emit less NOx and CO when compared to hydrous ethanol, while unburned hydrocarbon emissions increase due to the consequent worsening in fuel combustion. © 2018 SAE International. All Rights Reserved.

关键词： Ethanol

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