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17 pages, 525 KB  
Review
Towards Carbon-Neutral Hydrogen: Integrating Methane Pyrolysis with Geothermal Energy
by Ayann Tiam, Marshall Watson and Talal Gamadi
Processes 2025, 13(10), 3195; https://doi.org/10.3390/pr13103195 - 8 Oct 2025
Abstract
Methane pyrolysis produces hydrogen (H2) with solid carbon black as a co-product, eliminating direct CO2 emissions and enabling a low-carbon supply when combined with renewable or low-carbon heat sources. In this study, we propose a hybrid geothermal pyrolysis configuration in [...] Read more.
Methane pyrolysis produces hydrogen (H2) with solid carbon black as a co-product, eliminating direct CO2 emissions and enabling a low-carbon supply when combined with renewable or low-carbon heat sources. In this study, we propose a hybrid geothermal pyrolysis configuration in which an enhanced geothermal system (EGS) provides base-load preheating and isothermal holding, while either electrical or solar–thermal input supplies the final temperature rise to the catalytic set-point. The work addresses four main objectives: (i) integrating field-scale geothermal operating envelopes to define heat-integration targets and duty splits; (ii) assessing scalability through high-pressure reactor design, thermal management, and carbon separation strategies that preserve co-product value; (iii) developing a techno-economic analysis (TEA) framework that lists CAPEX and OPEX, incorporates carbon pricing and credits, and evaluates dual-product economics for hydrogen and carbon black; and (iv) reorganizing state-of-the-art advances chronologically, linking molten media demonstrations, catalyst development, and integration studies. The process synthesis shows that allocating geothermal heat to the largest heat-capacity streams (feed, recycle, and melt/salt hold) reduces electric top-up demand and stabilizes reactor operation, thereby mitigating coking, sintering, and broad particle size distributions. High-pressure operation improves the hydrogen yield and equipment compactness, but it also requires corrosion-resistant materials and careful thermal-stress management. The TEA indicates that the levelized cost of hydrogen is primarily influenced by two factors: (a) electric duty and the carbon intensity of power, and (b) the achievable price and specifications of the carbon co-product. Secondary drivers include the methane price, geothermal capacity factor, and overall conversion and selectivity. Overall, geothermal-assisted methane pyrolysis emerges as a practical pathway to turquoise hydrogen, if the carbon quality is maintained and heat integration is optimized. The study offers design principles and reporting guidelines intended to accelerate pilot-scale deployment. Full article
21 pages, 19840 KB  
Article
Development of a Reduced Order Model for Turbine Blade Cooling Design
by Andrea Pinardi, Noraiz Mushtaq and Paolo Gaetani
Int. J. Turbomach. Propuls. Power 2025, 10(4), 37; https://doi.org/10.3390/ijtpp10040037 - 8 Oct 2025
Abstract
Rotating detonation engines (RDEs) are expected to have higher specific work and efficiency, but the high-temperature transonic flow delivered by the combustor poses relevant design and technological difficulties. This work proposes a 1D model for turbine internal cooling design which can be used [...] Read more.
Rotating detonation engines (RDEs) are expected to have higher specific work and efficiency, but the high-temperature transonic flow delivered by the combustor poses relevant design and technological difficulties. This work proposes a 1D model for turbine internal cooling design which can be used to explore multiple design options during the preliminary design of the cooling system. Being based on an energy balance applied to an infinitesimal control volume, the model is general and can be adapted to other applications. The model is applied to design a cooling system for a pre-existing stator blade geometry. Both the inputs and the outputs of the 1D simulation are in good agreement with the values found in the literature. Subsequently, 1D results are compared to a full conjugate heat transfer (CHT) simulation. The agreement on the internal heat transfer coefficient is excellent and is entirely within the uncertainty of the correlation. Despite some criticality in finding agreement with the thermal power distribution, the Mach number, the total pressure drop, and the coolant temperature increase in the cooling channels are accurately predicted by the 1D code, thus confirming its value as a preliminary design tool. To guarantee the integrity of the blade at the extremities, a cooling solution with coolant injection at the leading and trailing edge is studied. A finite element analysis of the cooled blade ensures the structural feasibility of the cooling system. The computational economy of the 1D code is then exploited to perform a global sensitivity analysis using a polynomial chaos expansion (PCE) surrogate model to compute Sobol’ indices. Full article
16 pages, 6351 KB  
Article
The Role of La–Ti–Al–O Complex Inclusions in Microstructure Refinement and Toughness Enhancement of the Coarse-Grained Heat-Affected Zone in High-Heat-Input Welding
by Qiuming Wang, Jiangli He, Qingfeng Wang and Riping Liu
Metals 2025, 15(10), 1105; https://doi.org/10.3390/met15101105 - 3 Oct 2025
Viewed by 167
Abstract
The low-temperature impact properties of high-heat-input steels, particularly low-carbon Nb–Ti steel, are significantly influenced by the coarse-grained heat-affected zone (CGHAZ) in welded joints. The microstructure predominantly consists of granular bainitic ferrite (GBF), ferrite side plate (FSP), degenerate pearlite (DP), coarse plate-like ferrite (PF), [...] Read more.
The low-temperature impact properties of high-heat-input steels, particularly low-carbon Nb–Ti steel, are significantly influenced by the coarse-grained heat-affected zone (CGHAZ) in welded joints. The microstructure predominantly consists of granular bainitic ferrite (GBF), ferrite side plate (FSP), degenerate pearlite (DP), coarse plate-like ferrite (PF), and limited acicular ferrite (AF). This study investigates the effect of lanthanum (La) addition to Nb–Ti steel, leading to the formation of composite inclusions with a LaAlO3·TiN core surrounded by MnS/MnC precipitates. Unlike conventional Al2O3·MnS inclusions in Nb–Ti steel, these La-modified inclusions promote enhanced AF nucleation. This not only refines prior austenite grains but also reduces detrimental microstructural constituents such as GBF and FSP. As a result, the impact energy at −40 °C significantly improves from 23 J (Nb–Ti steel) to 137 J (Nb–Ti–La steel). Moreover, the inclusions exhibit an increase in size but a decrease in number density. The Nb–Ti–La variant demonstrates a higher AF volume fraction and increased AF density within the CGHAZ. The refined grain structure, along with an increased proportion of high-angle grain boundaries, effectively impedes secondary crack propagation. These microstructural modifications contribute to a substantial improvement in the low-temperature impact toughness of welded joints. Full article
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18 pages, 3387 KB  
Article
Machine Learning-Assisted Reconstruction of In-Cylinder Pressure in Internal Combustion Engines Under Unmeasured Operating Conditions
by Qiao Huang, Tianfang Xie and Jinlong Liu
Energies 2025, 18(19), 5235; https://doi.org/10.3390/en18195235 - 2 Oct 2025
Viewed by 186
Abstract
In-cylinder pressure provides critical insights for analyzing and optimizing combustion in internal combustion engines, yet its acquisition across the full operating space requires extensive testing, while physics-based models are computationally demanding. Machine learning (ML) offers an alternative, but its application to direct reconstruction [...] Read more.
In-cylinder pressure provides critical insights for analyzing and optimizing combustion in internal combustion engines, yet its acquisition across the full operating space requires extensive testing, while physics-based models are computationally demanding. Machine learning (ML) offers an alternative, but its application to direct reconstruction of full pressure traces remains limited. This study evaluates three strategies for reconstructing cylinder pressure under unmeasured operating conditions, establishing a machine learning-assisted framework that generates the complete pressure–crank angle (P–CA) trace. The framework treats crank angle and operating conditions as inputs and predicts either pressure directly or apparent heat release rate (HRR) as an intermediate variable, which is then integrated to reconstruct pressure. In all approaches, discrete pointwise predictions are combined to form the full P–CA curve. Direct pressure prediction achieves high accuracy for overall traces but underestimates HRR-related combustion features. Training on HRR improves combustion representation but introduces baseline shifts in reconstructed pressure. A hybrid approach, combining non-combustion pressure prediction with combustion-phase HRR-based reconstruction delivers the most robust and physically consistent results. These findings demonstrate that ML can efficiently reconstruct in-cylinder pressure at unmeasured conditions, reducing experimental requirements while supporting combustion diagnostics, calibration, and digital twin applications. Full article
(This article belongs to the Section I2: Energy and Combustion Science)
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17 pages, 6517 KB  
Article
Investigation of Process and Properties of Cu-Mn-Al Alloy Cladding Deposited on 27SiMn Steel via Cold Metal Transfer
by Jin Peng, Shihua Xie, Junhai Xia, Xingxing Wang, Zenglei Ni, Pei Wang and Nannan Chen
Crystals 2025, 15(10), 858; https://doi.org/10.3390/cryst15100858 - 30 Sep 2025
Viewed by 197
Abstract
This study systematically investigates the effects of welding current on the macro-morphology, microstructure, mechanical properties, and corrosion resistance of Cu-Mn-Al alloy coatings deposited on 27SiMn steel substrates using Cold Metal Transfer (CMT) technology. The 27SiMn steel is widely applied in coal mining, geology, [...] Read more.
This study systematically investigates the effects of welding current on the macro-morphology, microstructure, mechanical properties, and corrosion resistance of Cu-Mn-Al alloy coatings deposited on 27SiMn steel substrates using Cold Metal Transfer (CMT) technology. The 27SiMn steel is widely applied in coal mining, geology, and engineering equipment due to its high strength and toughness, but its poor corrosion and wear resistance significantly limits service life. To address this issue, a Cu-Mn-Al alloy (high-manganese aluminum bronze) was selected as a cladding material because of its superior combination of mechanical strength, toughness, and excellent corrosion resistance in saline and marine environments. Compared with conventional cladding processes, CMT technology enables low-heat-input deposition, reduces dilution from the substrate, and promotes defect-free coating formation. To the best of our knowledge, this is the first report on the fabrication of Cu-Mn-Al coatings on 27SiMn steel using CMT, aiming to optimize process parameters and establish the relationship between welding current, phase evolution, and coating performance. The experimental results demonstrate that the cladding layer width increases progressively with welding current, whereas the layer height remains relatively stable at approximately 3 mm. At welding currents of 120 A and 150 A, the cladding layer primarily consists of α-Cu, κII, β-Cu3Al, and α-Cu + κIII phases. At higher welding currents (180 A and 210 A), the α-Cu + κIII phase disappears, accompanied by the formation of petal-shaped κI phase. The peak shear strength (509.49 MPa) is achieved at 120 A, while the maximum average hardness (253 HV) is obtained at 150 A. The 120 A cladding layer demonstrates optimal corrosion resistance. These findings provide new insights into the application of CMT in fabricating Cu-Mn-Al protective coatings on steel and offer theoretical guidance for extending the service life of 27SiMn steel components in aggressive environments. Full article
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37 pages, 4235 KB  
Article
Optimization-Based Exergoeconomic Assessment of an Ammonia–Water Geothermal Power System with an Elevated Heat Source Temperature
by Asli Tiktas
Energies 2025, 18(19), 5195; https://doi.org/10.3390/en18195195 - 30 Sep 2025
Viewed by 301
Abstract
Geothermal energy has been recognized as a promising renewable resource for sustainable power generation; however, the efficiency of conventional geothermal power plants has remained relatively low, and high investment costs have limited their competitiveness with other renewable technologies. In this context, the present [...] Read more.
Geothermal energy has been recognized as a promising renewable resource for sustainable power generation; however, the efficiency of conventional geothermal power plants has remained relatively low, and high investment costs have limited their competitiveness with other renewable technologies. In this context, the present study introduced an innovative geothermal electricity generation system aimed at enhancing energy efficiency, cost-effectiveness, and sustainability. Unlike traditional configurations, the system raised the geothermal source temperature passively by employing advanced heat transfer mechanisms, eliminating the need for additional energy input. Comprehensive energy, exergy, and exergoeconomic analyses were carried out, revealing a net power output of 43,210 kW and an energy efficiency of 30.03%, notably surpassing the conventional Kalina cycle’s typical 10.30–19.48% range. The system’s annual electricity generation was 11,138.53 MWh, with an initial investment of USD 3.04 million and a short payback period of 3.20 years. A comparative assessment confirmed its superior thermoeconomic performance. In addition to its technoeconomic advantages, the environmental performance of the proposed configuration was quantified. A streamlined life cycle assessment (LCA) was performed with a functional unit of 1 MWh of net electricity. The proposed system exhibited a carbon footprint of 20–60 kg CO2 eq MWh−1 (baseline: 45 kg CO2 eq MWh−1), corresponding to annual emissions of 0.22–0.67 kt CO2 eq for the simulated output of 11,138.53 MWh. Compared with coal- and gas-fired plants of the same capacity, avoided emissions of approximately 8.6 kt and 5.0 kt CO2 eq per year were achieved. The water footprint was determined as ≈0.10 m3 MWh−1 (≈1114 m3 yr−1), which was substantially lower than the values reported for fossil technologies. These findings confirmed that the proposed system offered a sustainable alternative to conventional geothermal and fossil-based electricity generation. Multi-objective optimization using NSGA-II was carried out to maximize energy and exergy efficiencies while minimizing total cost. Key parameters such as turbine inlet temperature (459–460 K) and ammonia concentration were tuned for performance stability. A sensitivity analysis identified the heat exchanger, the first condenser (Condenser 1), and two separators (Separator 1, Separator 2) as influential on both performance and cost. The exergoeconomic results indicated Separator 1, Separator 2, and the turbine as primary locations of exergy destruction. With an LCOE of 0.026 USD/kWh, the system emerged as a cost-effective and scalable solution for sustainable geothermal power production without auxiliary energy demand. Full article
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17 pages, 650 KB  
Article
Optimization of Biomass Delivery Through Artificial Intelligence Techniques
by Marta Wesolowska, Dorota Żelazna-Jochim, Krystian Wisniewski, Jaroslaw Krzywanski, Marcin Sosnowski and Wojciech Nowak
Energies 2025, 18(18), 5028; https://doi.org/10.3390/en18185028 - 22 Sep 2025
Viewed by 313
Abstract
Efficient and cost-effective biomass logistics remain a significant challenge due to the dynamic and nonlinear nature of supply chains, as well as the scarcity of comprehensive data on this topic. As biomass plays an increasingly important role in sustainable energy systems, managing its [...] Read more.
Efficient and cost-effective biomass logistics remain a significant challenge due to the dynamic and nonlinear nature of supply chains, as well as the scarcity of comprehensive data on this topic. As biomass plays an increasingly important role in sustainable energy systems, managing its complex supply chains efficiently is crucial. Traditional logistics methods often struggle with the dynamic, nonlinear, and data-scarce nature of biomass supply, especially when integrating local and international sources. To address these challenges, this study aims to develop an innovative modular artificial neural network (ANN)-based Biomass Delivery Management (BDM) model to optimize biomass procurement and supply for a fluidized bed combined heat and power (CHP) plant. The comprehensive model integrates technical, economic, and geographic parameters to enable supplier selection, optimize transport routes, and inform fuel blending strategies, representing a novel approach in biomass logistics. A case study based on operational data confirmed the model’s ability to identify cost-effective and quality-compliant biomass sources. Evaluated using empirical operational data from a Polish CHP plant, the ANN-based model demonstrated high predictive accuracy (MAE = 0.16, MSE = 0.02, R2 = 0.99) within the studied scope. The model effectively handled incomplete datasets typical of biomass markets, aiding in supplier selection decisions and representing a proof-of-concept for optimizing Central European biomass logistics. The model was capable of generalizing supplier recommendations based on input variables, including biomass type, unit price, and annual demand. The proposed framework supports both strategic and real-time logistics decisions, providing a robust tool for enhancing supply chain transparency, cost efficiency, and resilience in the renewable energy sector. Future research will focus on extending the dataset and developing hybrid models to strengthen supply chain stability and adaptability under varying market and regulatory conditions. Full article
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13 pages, 2169 KB  
Article
Controlled Formation of Nanoislands During Microwave Annealing of Au Thin Films
by Ali Ghanim Gatea Al-Rubaye, Alaa Alasadi, Khalid Rmaydh Muhammed and Catalin-Daniel Constantinescu
Metals 2025, 15(9), 1030; https://doi.org/10.3390/met15091030 - 18 Sep 2025
Viewed by 441
Abstract
We present a systematic study on the fabrication of gold nanoislands by microwave-assisted annealing, a rapid and energy-efficient alternative to conventional thermal treatments. Gold thin films with nominal thicknesses of 4, 5, 6, 8, and 10 nm are deposited by thermal evaporation directly [...] Read more.
We present a systematic study on the fabrication of gold nanoislands by microwave-assisted annealing, a rapid and energy-efficient alternative to conventional thermal treatments. Gold thin films with nominal thicknesses of 4, 5, 6, 8, and 10 nm are deposited by thermal evaporation directly onto BK7 glass substrates, with and without a 3 nm chromium adhesion layer. The samples are subsequently annealed in a microwave kiln, where microwave irradiation is absorbed and converted to heat within the graphite-coated cavity (kiln), allowing the substrate temperature to exceed 550 °C, the threshold required for film dewetting. This process induces a controlled morphological evolution from continuous thin films to well-defined nanoislands, with the final size distribution strongly dependent on the initial film thickness. Compared with oven-based annealing, microwave treatment promotes faster and more uniform heating, which enhances atomic diffusion and accelerates dewetting while reducing the risk of substrate deformation or excessive coalescence. The resulting nanoislands exhibit tailored size-dependent plasmonic properties, with clear correlations between film thickness, crystallite size, and optical absorption features. Importantly, the method is cost-efficient, requiring shorter processing times and lower energy input, while enabling reproducible fabrication of high-quality plasmonic nanostructures on inexpensive glass substrates, suitable for applications in sensing, photonics, and nanophotonics. Full article
(This article belongs to the Special Issue Metallic Nanostructured Materials and Thin Films)
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22 pages, 4596 KB  
Review
Microwave Synthesis in Zeolite and MOF Membranes
by Liangqing Li
Membranes 2025, 15(9), 275; https://doi.org/10.3390/membranes15090275 - 12 Sep 2025
Viewed by 673
Abstract
Zeolites and metal–organic frameworks (MOFs) are crystalline porous materials characterized by highly ordered pore structures. Their fabrication into membranes has demonstrated significant potential for use in separation processes involving liquids or gases. Traditional methods for synthesizing these membranes often require prolonged reaction times [...] Read more.
Zeolites and metal–organic frameworks (MOFs) are crystalline porous materials characterized by highly ordered pore structures. Their fabrication into membranes has demonstrated significant potential for use in separation processes involving liquids or gases. Traditional methods for synthesizing these membranes often require prolonged reaction times and high energy input. In contrast, microwave heating technology has gained increasing attention as a more efficient approach for the synthesis of zeolite and MOF membranes, offering advantages such as rapid and uniform heating, enhanced energy efficiency, and greater environmental sustainability. This review focuses on fundamental research and laboratory-scale studies on the microwave-assisted synthesis of zeolite and MOF membranes. It begins by outlining the principles of microwave heating, emphasizing the mechanisms that enable accelerated heating. The discussion then highlights the key features and advantages of microwave synthesis in membrane fabrication, including reduced synthesis times, thinner membrane layers, suppression of impurities and undesired phases, and enhanced membrane density. Recent advancements in this area are also presented, particularly strategies for optimizing microwave heating processes, such as the use of single-mode microwave systems and precise control of heating rates. Notably, optimized microwave synthesis with controlled heating rates has been shown to reduce crystallization time by approximately 69%, decrease membrane thickness by nearly 70%, and improve pervaporation flux for acetic acid dehydration by more than 70%, compared with conventional microwave synthesis of mordenite membranes. Finally, the review summarizes and presents future perspectives aimed at promoting continued research and refinement of synthesis strategies in this promising area. Full article
(This article belongs to the Special Issue Design, Synthesis, and Application of Inorganic Membranes)
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28 pages, 58198 KB  
Article
Numerical Investigation of Ultra-Long Gravity Heat Pipe Systems for Geothermal Power Generation at Mount Meager
by Yutong Chai, Wenwen Cui, Ao Ren, Soheil Asgarpour and Shunde Yin
Mining 2025, 5(3), 55; https://doi.org/10.3390/mining5030055 - 9 Sep 2025
Viewed by 836
Abstract
The Super-long Gravity Heat Pipe (SLGHP) is an efficient geothermal energy utilization technology that can transmit thermal energy by fully utilizing natural temperature differences without external energy input. This study focuses on the high-altitude geothermal environment of Mount Meager, Canada, and employs numerical [...] Read more.
The Super-long Gravity Heat Pipe (SLGHP) is an efficient geothermal energy utilization technology that can transmit thermal energy by fully utilizing natural temperature differences without external energy input. This study focuses on the high-altitude geothermal environment of Mount Meager, Canada, and employs numerical simulations and dynamic thermal analysis to systematically investigate the thermal transport performance of the SLGHP system under both steady-state and dynamic operating conditions. The study also examines the impact of various structural parameters on the system’s performance. Three-dimensional CFD simulations were conducted to analyze the effects of pipe diameter, length, filling ratio, working fluid selection, and pipe material on the heat transfer efficiency and heat flux distribution of the SLGHP. The results indicate that working fluids such as CO2 and NH3 significantly enhance the heat flux density, while increasing pipe diameter may reduce the amount of liquid retained in the condenser section, thereby affecting condensate return and thermal stability. Furthermore, dynamic thermal analysis using a three-node RC network model simulated the effects of diurnal temperature fluctuations and variations in the convective heat transfer coefficient in the condenser section on system thermal stability. The results show that the condenser heat flux can reach a peak of 5246 W/m2 during the day, while maintaining a range of 2200–2600 W/m2 at night, with the system exhibiting good thermal responsiveness and no significant lag or flow interruption. In addition, based on the thermal output of the SLGHP system and the integration with the Organic Rankine Cycle (ORC) system, the power generation potential analysis indicates that the system, with 100 heat pipes, can provide stable power generation of 50–60 kW. In contrast to previous SLGHP studies focused on generalized modeling, this work introduces a site-specific CFD–RC framework, quantifies structural sensitivity via heat flux indices, and bridges numerical performance with economic feasibility, offering actionable insights for high-altitude deployment. This system has promising practical applications, particularly for providing stable renewable power in remote and cold regions. Future research will focus on field experiments and system optimization to further improve system efficiency and economic viability. Full article
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24 pages, 2759 KB  
Article
Heat Source Parameter Identification Based on Attention-Enhanced Residual Convolutional Neural Network
by Hao Jiang, Xinyu Liu, Zhenfei Guo, Tianlei Yang, Mengyi Chen, Zongzhe Man, Xiao Wei, Jiangfan Zhou and Da Liu
Materials 2025, 18(17), 4174; https://doi.org/10.3390/ma18174174 - 5 Sep 2025
Viewed by 817
Abstract
Heat source parameters are critical input variables in welding thermal analysis, directly and significantly affecting the accuracy of the temperature field distribution, welding distortion, and residual stress prediction. This is particularly important in safety-critical welded structures, where high-precision heat source parameter identification is [...] Read more.
Heat source parameters are critical input variables in welding thermal analysis, directly and significantly affecting the accuracy of the temperature field distribution, welding distortion, and residual stress prediction. This is particularly important in safety-critical welded structures, where high-precision heat source parameter identification is essential for ensuring the thermal simulation accuracy and mechanical performance reliability. Traditional parameter identification methods based on finite element simulations or experiments have limitations in adapting to complex working conditions and variable environments. To address this, this paper proposes the Heat Source Parameter Identification Network (HSPINet) model based on a residual convolutional neural network (ResNet) architecture with an attention mechanism capable of extracting key features from the weld morphology of T-joint structures, while accounting for the influence of process parameters and joint dimensions to achieve efficient and accurate identification of heat source parameters. This study not only enhances the intelligence level of heat source parameter identification but also provides a practical, intelligent tool for welding simulation and thermal field evaluation in complex industrial applications, demonstrating significant theoretical value and broad applicability in laser processing and manufacturing scenarios. Full article
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18 pages, 4673 KB  
Article
Influence of Electrical Parameters in a Composite Wing Actuated by Shape Memory Alloys Wires: A Numerical–Experimental Study
by Miriam Battaglia, Valerio Acanfora and Aniello Riccio
J. Compos. Sci. 2025, 9(9), 460; https://doi.org/10.3390/jcs9090460 - 1 Sep 2025
Viewed by 810
Abstract
This study investigates the influence of electrical actuation parameters on the performance of a morphing composite aerodynamic profile actuated by Shape Memory Alloy (SMA) wires. A fully coupled electro-thermo-mechanical finite element model has been developed to simulate the transient response of NiTi SMA, [...] Read more.
This study investigates the influence of electrical actuation parameters on the performance of a morphing composite aerodynamic profile actuated by Shape Memory Alloy (SMA) wires. A fully coupled electro-thermo-mechanical finite element model has been developed to simulate the transient response of NiTi SMA, capturing the nonlinear interplay between temperature evolution, phase transformation, and mechanical deformation under Joule heating. The model incorporates phase-dependent material properties, heat effects, and geometric constraints, enabling accurate prediction of actuation dynamics. To validate the model, a morphing spoiler prototype has been fabricated using high-performance additive manufacturing with a carbon fibre-reinforced polymer. The SMA wires have been pretensioned and electrically actuated at different current levels (3 A and 6 A), and the resulting deformation has been recorded through video analysis with embedded timers. Experimental measurements confirmed the model’s ability to predict both actuation time and displacement, with maximum deflections of 33 mm and 40 mm corresponding to different current inputs. This integrated approach demonstrates an efficient and compact solution for active aerodynamic surfaces without the need for mechanical linkages, enabling future developments in adaptive structures for automotive and aerospace applications. Full article
(This article belongs to the Special Issue Metal Composites, Volume II)
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16 pages, 3808 KB  
Article
Reducing Heat Without Impacting Quality: Optimizing Trypsin Inhibitor Inactivation Process in Low-TI Soybean
by Ruoshi Xiao, Luciana Rosso, Troy Walker, Patrick Reilly, Bo Zhang and Haibo Huang
Foods 2025, 14(17), 3039; https://doi.org/10.3390/foods14173039 - 29 Aug 2025
Viewed by 754
Abstract
A soybean meal is a key protein source in human foods and animal feed, yet its digestibility is constrained by endogenous trypsin inhibitors (TIs). Thermal processing is the mainstream tool for TI inactivation, but high-intensity heat treatments increase energy consumption and can potentially [...] Read more.
A soybean meal is a key protein source in human foods and animal feed, yet its digestibility is constrained by endogenous trypsin inhibitors (TIs). Thermal processing is the mainstream tool for TI inactivation, but high-intensity heat treatments increase energy consumption and can potentially denature proteins, diminishing nutritional quality. Reducing the thermal input while maintaining nutritional quality is, therefore, a critical challenge. One promising strategy is the use of soybean cultivars bred for low-TI expression, which may allow for milder processing. However, the performance of these low-TI cultivars under reduced heat conditions remains unstudied. This study treated soybean samples under four different temperatures (60, 80, 100, and 121 °C) for 10 min and investigated the impact of heat treatment on TI concentration, in vitro protein digestibility, and nutritional properties of meals from a conventional high-TI variety (Glenn) and a novel low-TI variety (VT Barrack). Results showed that heat treatment at 100 °C significantly improved protein digestibility and lower TI concentrations in both varieties. A negative correlation was observed between protein digestibility and TI concentration in both soybean varieties. At 100 °C, the low-TI variety achieved 81.4% protein digestibility with only 0.6 mg/g TIs, whereas the high-TI variety required 121 °C to achieve comparable protein digestibility and a TI reduction. These findings highlight that low-TI soybeans can lower the necessary thermal treatment to 100 °C to minimize TIs while simultaneously preserving protein quality and cutting energy demand, offering a practical, cost-effective approach to producing higher-quality soybean meals. Full article
(This article belongs to the Section Food Physics and (Bio)Chemistry)
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22 pages, 17668 KB  
Article
Enhancing the Aerodynamic Performance of Airfoils Using DBD Plasma Actuators: An Experimental Approach
by Eder Ricoy-Zárate, Horacio Martínez, Erik Rosado-Tamariz, Andrés Blanco-Ortega and Rafael Campos-Amezcua
Processes 2025, 13(9), 2725; https://doi.org/10.3390/pr13092725 - 26 Aug 2025
Viewed by 1123
Abstract
This research presents an experimental analysis of the influence of atmospheric pressure plasma on the performance of a micro horizontal-axis wind turbine blade. The investigation was conducted using an NACA 4412 airfoil equipped with a dielectric barrier discharge (DBD) plasma actuator. The electrodes [...] Read more.
This research presents an experimental analysis of the influence of atmospheric pressure plasma on the performance of a micro horizontal-axis wind turbine blade. The investigation was conducted using an NACA 4412 airfoil equipped with a dielectric barrier discharge (DBD) plasma actuator. The electrodes were configured asymmetrically, with a 2 mm gap and copper electrodes that are 0.20 mm in thickness. A high voltage of 6 kV was applied, resulting in a current of 0.071 mA and a power output of 0.426 W. Optical emission spectroscopy identified the excited components through the interaction of the high-voltage AC electric field with air molecules: N2, N2+, O2+, and O. The electrohydrodynamic force mainly results from the observed charged ions that, when accelerated by the electric field, transfer momentum to neutral molecules via collisions, leading to the formation of the observed jet plasma. The findings indicated a notable enhancement in aerodynamic performance attributable to the electrohydrodynamic (EHD) flow generated by the plasma. The estimated electrohydrodynamic force (8.712×104 N) is capable of maintaining the flow attached to the airfoil surface, thereby augmenting flow circulation and, consequently, enhancing the lift force. According to blade element theory, the lift and drag coefficients directly influence the torque and mechanical power generated by the wind turbine rotor. Schlieren imaging was utilized to observe alterations in air density and flow patterns. Lissajous curve analysis was used to examine the electrical discharge behavior, showing that only 7.04% of the input power was converted into heat. This indicates that nearly all input electric energy was transformed into EHD force by the atmospheric pressure plasma. Compared to traditional aerodynamic control methods, DBD actuators are a feasible alternative for small wind turbines due to their lightweight design, absence of moving parts, ability to be surface-embedded without altering blade geometry, and capacity to generate active, dynamic flow control with reduced energy consumption. Full article
(This article belongs to the Special Issue Modeling and Optimization for Multi-scale Integration)
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21 pages, 2871 KB  
Article
Numerical Investigation of Factors Influencing the Formation of Thermal Stratification in Water Bodies
by Zhenglong Du, Yun Wang, Zhiben Shen, Shiping He and Jun Tan
Appl. Sci. 2025, 15(17), 9301; https://doi.org/10.3390/app15179301 - 24 Aug 2025
Viewed by 592
Abstract
Controlled thermal stratification in water is crucial for applications such as testing the thermal stealth of underwater vehicles and studying aquatic ecosystems. However, existing laboratory methods for generating such stratified environments often lack stability and uniformity. This study systematically investigates the influence of [...] Read more.
Controlled thermal stratification in water is crucial for applications such as testing the thermal stealth of underwater vehicles and studying aquatic ecosystems. However, existing laboratory methods for generating such stratified environments often lack stability and uniformity. This study systematically investigates the influence of various hot water injection methods on the stability of thermal stratification. A computational fluid dynamics model, incorporating the overlapping dynamic mesh technique and the Volume of Fluid free-surface capturing method, was used to compare four generation strategies: single-side fixed discharge, towed horizontal discharge, towed vertical upward discharge, and multi-nozzle towed vertical upward discharge. The results indicate that towed discharge methods produce more stable and uniform thermal stratification compared to the fixed discharge method, achieving a 10.1% increase in the water body’s vertical stability coefficient and a 4.5% increase in the Richardson number, while the maximum surface temperature difference was significantly reduced from 0.98 K to 0.37 K. Among the towed methods, vertical upward discharge demonstrated superior stability over horizontal discharge, as it directly transports the high-temperature plume to the upper layer, minimizing thermal exchange with the lower layer, with its vertical stability coefficient and Richardson number being 17.9% and 23% higher, respectively. While maintaining a constant heat input per unit volume, the multi-nozzle configuration yielded N2 and Ri values comparable to the single-nozzle version, while further improving the temperature uniformity at the free surface. Consequently, the towed vertical upward discharge emerges as a highly efficient method for establishing stable and uniform thermal stratification, with the multi-nozzle configuration showing significant promise for large-scale applications. This study provides a valuable reference for creating stratified fluid environments and for related engineering fields. Full article
(This article belongs to the Special Issue Advances in Fluid Mechanics Analysis)
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