Search Results (10,260)

The growing need to mitigate climate change has accelerated the development of Carbon Capture, Utilization, and Storage (CCUS) technologies, where the safe transport of supercritical CO${}_2$ (sCO${}_2$) through pipelines is a key challenge. The flow behavior in such systems is strongly influenced by phase-change processes under transient conditions such as decompression and heat transfer and is further complicated by the presence of impurities (e.g., N${}_2$, CH${}_4$, and Ar). These impurities modify thermodynamic properties and phase boundaries, thereby affecting the overall flow dynamics. In this study, the influence of impurities on leakage, mass flow rate, and decompression wave propagation in sCO${}_2$ pipelines is investigated using computational fluid dynamics (CFD) simulations. A real-fluid model (RFM) implemented in the CONVERGE CFD solver is employed, with a tabulation-based approach to accurately capture thermodynamic and transport properties across multiphase regimes. The simulations were validated against available experimental data and performed for varying impurity concentrations to assess their impact on key flow variables, including pressure, temperature, and wave speed. Although simplifying assumptions were used, the results are in fairly good agreement with experimental observations and provide a better understanding of the phase behavior induced by impurities during transient decompression. Additionally, the effects of outlet geometry, pipeline configuration, and the choice of equation of state are examined, highlighting their influence on the predicted flow response. The validity of the RFM modeling framework is further demonstrated by simulations of a large-scale pipeline configuration representative of industrial conditions, which will serve as a benchmark for future improvements. Full article

Aluminum–vanadium (Al–V) master alloy is a key raw material for manufacturing high-end alloys, but the internal temperature transient field during its self-propagating high-temperature synthesis (SHS) is nearly impossible to measure in situ. This work develops a numerical simulation framework for Al–V master alloy SHS, featuring a novel temperature–time dual-criteria adaptive moving heat source and a gas–liquid–solid three-phase heat transfer model coupled with temperature-dependent thermophysical properties. The model, implemented in ANSYS Fluent via a customized user-defined function (UDF), is experimentally validated with a maximum temperature error below 7%. Results reveal that higher compact relative density accelerates combustion wave propagation, while increased slagging agent content exerts an inhibitory effect. This study provides a theoretical and quantitative tool for mechanism analysis and industrial process optimization of Al–V master alloy SHS production. Full article

Gypsum-based fire protection relies on thermally activated dehydration, where chemically bound water is released and evaporated, thereby providing an endothermic heat sink that delays heat penetration through assemblies. In parallel, inorganic hydrated salts are increasingly used as flame-retardant additives in gypsum-based systems to enhance heat absorption over specific temperature ranges. Fire simulation tools and performance-based fire engineering approaches require reliable kinetic data and reaction enthalpies that can be implemented as coupled thermal–chemical source terms. However, additive-specific kinetic datasets remain limited, particularly under restricted vapor exchange conditions representative of porous construction materials. This work investigates the thermal decomposition behavior and dehydration kinetics of Aluminum Trihydrate (Al(OH)₃, ATH), Magnesium Hydroxide (Mg(OH)₂, MDH), Calcium Aluminate Sulfate (3CaO·Al₂O₃·3CaSO₄·32H₂O, CAS), and Magnesium Sulfate Heptahydrate (MgSO₄·7H₂O, ESM) with emphasis on vapor-restricted conditions representative of confined porous systems. Differential scanning calorimetry (DSC) experiments were conducted at three heating rates (2, 10, and 20 K/min for MDH, CAS and ESM and 20, 40 and 60 K/min for GB-ATH) up to 600 °C using pinhole crucibles to simulate autogenous vapor pressure. The thermal analysis indicates that ATH and MDH exhibit predominantly single-step dehydration behavior, while ESM shows a complex multi-step mechanism. Although CAS presents a single dominant thermal peak in the DSC signal, the isoconversional analysis reveals a multi-stage reaction behavior, demonstrating that peak-based interpretation alone may be insufficient for such systems. Kinetic parameters were determined using both model-free (Starink) and model-fitting approaches in accordance with the recommendations of the Kinetics Committee of the International Confederation for Thermal Analysis and Calorimetry (ICTAC). All reactions were consistently described using the Avrami–Erofeev model as an effective phenomenological representation of the conversion behavior. The extracted kinetic triplets were validated through numerical simulations, showing good agreement with experimental conversion and reaction rate data. The resulting kinetic parameters and dehydration enthalpies provide a physically consistent dataset for the description of dehydration processes under restricted vapor exchange. These results support the development of thermochemical models for gypsum-based systems; however, their transferability to full-scale assemblies remains subject to validation under coupled heat- and mass-transfer conditions. Full article

The photothermal effect is an important part of biological tissue optics. The reasonable use of temperature changes caused by the photothermal effect is of great value for the treatment of lesions. However, it is not easy to measure changes in light and heat temperatures in tissues experimentally. This paper combines Monte Carlo simulation and finite-element numerical calculation based on the Pennes biological tissue heat transfer equation to simulate light transmission and distributions of light and heat in biological tissues, including single-layer uniform biological tissue simulations and a classic three-layer skin optical model. Through the simulation of single-layer uniform biological tissue, the overall trend and range of biological tissue temperature change under different parameters are obtained in this work. Third, in the classic three-layer skin optical model simulation, this work combines a data-fitting method to derive a formula relating internal temperature and tissue depth to the absorption coefficient. Compared with the simulation standard results, the error of the above fitting formula is within 1.2%, and it can be applied in the field of photothermal therapy in the future to help medical workers understand the range of temperature changes in biological tissues. Full article

HfO₂ films have become a critical component for advanced electronics and a wide range of applications. However, their implementation requires control of their microstructure and defects, which often act as charge carrier traps, leading to leakage current in devices and hindering their dielectric properties. Here, we deposit HfO₂ thin films by atomic layer deposition (ALD) on sapphire, Ga₂O₃, and InGaO₃ substrates at low temperature and investigate the dependence of their crystal structure on substrate type, annealing, and thickness. X-ray diffraction measurements showed that alloying Ga₂O₃ with a modest amount of Indium transferred HfO₂ films from amorphous to polycrystalline, an important finding that may be applicable to the deposition of other material systems. The study also presents an interesting approach to measuring shallow and deep traps formed in the films and shows how to control their levels and distributions in the band gap. The measurements reveal that the difference in band gap between the substrate and film, as well as the presence of impurities, strongly influences trap densities and depths. Electron paramagnetic resonance (EPR) measurements were performed to probe the electronic structure of specific point defects detectable by EPR and to correlate these results with trap measurements. Full article

This article presents the potential for maliciously influencing a control system by interfering with the program code of an industrial controller, using a temperature control system for a heating process based on resistive electric heating as an example. The presented attack scenarios are crucial for the energy efficiency of electric heating systems, which is related to the issue of cybersecurity in the area of energy security. The aim of this research was to demonstrate that a cyberattack involving the malicious manipulation of the setpoint can be carried out in a manner invisible to the heating process operator and be difficult to detect using classical time-domain control quality indicators (time-response specifications). The first involves incorporating proportional elements with mutually inverted gains into the input and output of a closed-loop system. The second method is based on adding an additional transfer function G_m(s) in parallel to the control system. The difference between the correct and manipulated setpoints is introduced into the input, and the output signal is added to the actual (hidden) value of the controlled variable. In the first method, at the moment of starting the control system, there is a difference between the apparent (falsified) value and the ambient temperature. In the second method, the inclusion of an additional G_m(s) ensures that the apparent (falsified) value of the controlled variable matches the temperature at the moment of starting the system. PID control enables achieving satisfactory control quality in heating processes, which are characterized by high inertia and time delays. Compared to classical PID regulation, advanced control methods can, under certain conditions, provide better performance in terms of quality indicators. However, due to their high computational complexity and sensitivity to model uncertainty—particularly in methods relying on accurate system identification—PID controllers continue to be widely used in industrial practice. For this reason, the present study focuses on a control system based on a PID controller as a practical solution. Based on the results, it was found that the most effective manipulation occurred within the range from 0.9 to 1.1 of the actual setpoint value for both the first and second method, using a model with $T_m$ between 5 s and 30 s. In these cases, the quality indicators referenced to the nominal values, determined for the falsified control system responses to a step change in the setpoint, were as follows: overshoot—0.97 and 1.30 (method 1), and 0.90 and 1.10 (method 2 for 5 s), 0.75 and 1.30 (method 2 for 30 s); settling time—1.06 (method 1), and 0.98 and 1.17 (method 2 for 5 s), 0.85 and 1.14 (method 2 for 30 s). The settling times determined for the system’s response to a disturbance were: 1.00 and 1.15 (method 1), and 1.13 and 1.16 (method 2 for 5 s), 1.12 and 1.02 (method 2 for 30 s). Based on the conducted analysis, it was demonstrated that the relatively simple setpoint manipulation methods presented can effectively mask the impact of malicious interference on the temperature value in the control system of a heating process. Full article

Anaerobic digesters operating under neotropical conditions face significant technological constraints. High humidity, intense solar radiation, and pronounced diurnal temperature variations increase conductive, convective, and radiative heat losses. These factors reduce internal thermal stability and directly affect methane production rates and overall energy efficiency. As a result, thermal instability becomes a recurrent operational bottleneck in biogas plants without active temperature control. This review examines the thermal and dynamic behavior of anaerobic reactors from a process-engineering perspective. It integrates energy balances, heat-transfer mechanisms, and computational fluid dynamics (CFD) modeling. The combined effects of temperature gradients, hydrodynamic mixing patterns, and structural material properties are analyzed to determine their influence on thermal homogeneity, microbial stability, and methane yield consistency under mesophilic conditions. Technological strategies to mitigate thermal losses are evaluated. These include passive insulation using low-conductivity materials, geometry optimization supported by numerical modeling, and thermal recirculation schemes, as these factors govern temperature distribution and process resilience. Current limitations are also discussed, particularly the frequent decoupling between ADM1-based kinetic models and transient heat-transfer analysis. This separation restricts predictive capability under real-scale diurnal temperature oscillations. The development and validation of coupled hydrodynamic–thermal–biokinetic models under fluctuating neotropical boundary conditions are proposed as critical steps. Such integrated approaches can enhance operational stability, ensure consistent methane production, and improve energy self-sufficiency in organic waste valorization systems. Full article

Maintaining stable molding quality in hydraulic injection molding machines is difficult because the internal state of molten resin cannot be directly observed and varies with material properties and operating conditions. This difficulty is intensified by variations in hydraulic characteristics caused by oil temperature changes. This study proposes an adaptive feedforward control (AFC) framework that improves injection velocity tracking while utilizing AFC learning parameters as indicators of resin state. AFC is implemented as a multi-frequency feedforward controller whose parameters are updated through repetitive injection cycles. To overcome the limited learning duration within a single injection shot, a shot-to-shot compensation mechanism accumulates and transfers learning results across consecutive shots. Experiments are conducted on a hydraulic injection molding machine using polypropylene materials with different viscosities. The results show that the converged AFC learning parameters vary systematically with material changes and correspond to differences in molded product appearance. Furthermore, by adjusting the cylinder temperature of another material, the AFC parameters converge to values close to those of a reference material, resulting in similar molded products. These findings demonstrate that AFC learning parameters reflect variations in resin state and can serve as practical state indicators for aligning molding conditions. Full article

Coffee processing requires continuous optimization to preserve sensory quality while improving process efficiency. Although hyperspectral imaging has been widely applied for food quality evaluation, its use for predicting coffee cup score during controlled drying remains limited. This study aimed to evaluate the effect of drying temperature on the drying kinetics of Caturra coffee and to develop a predictive model for cup score using hyperspectral imaging combined with Partial Least Squares Regression (PLSR). Coffee samples were dried at four constant temperatures (30, 40, 50, and 60 °C) in forced-convection ovens, and hyperspectral reflectance images (400–1000 nm) were acquired using a Specim FX10 camera. Sensory evaluation was conducted by six certified Q Arabica Graders. Drying times were 52, 34, 30, and 20 h at 30, 40, 50, and 60 °C, respectively, with corresponding cup scores of 83.21, 83.50, 83.60, and 83.26 points. Effective moisture diffusivity ranged from ${10}^{-13}$ to ${10}^{-12}$ m²/s, while mass transfer coefficients were on the order of ${10}^{-9}$ m/s, with activation energies of 28.016 and 19.272 kJ/mol. No significant differences in cup score were observed among drying temperatures ($p>0.05$). A PLSR-based model was developed to estimate cup score from hyperspectral data, achieving $R^2$ values of 0.770 and 0.855 and RMSE values of 0.515 and 0.518 for calibration and validation, respectively. Key wavelengths at 480, 600, 720, and 940 nm were identified as the most influential spectral regions associated with chemical compounds affecting sensory quality. These findings demonstrate the potential of integrating drying kinetics and hyperspectral imaging as a rapid and non-destructive approach for objective prediction of coffee sensory quality during processing. Full article

The thermal safety and longevity of lithium-ion batteries are critically constrained by excessive temperature rise and spatial thermal non-uniformity, particularly during high-rate discharges. Most existing numerical investigations rely on simplified heat generation models that fail to capture the spatiotemporal heterogeneity of electrochemical heat sources, leading to compromised predictive accuracy. To address this deficiency, this study develops a comprehensive three-dimensional electrochemical–thermal coupled framework, integrating the Newman pseudo-two-dimensional (P2D) electrochemical model with conjugate heat transfer and laminar flow dynamics. The predictive robustness of this framework is rigorously validated against experimental data across multiple discharge rates (3 C and 5 C). The validated model is then deployed to evaluate a water-cooled microchannel cold plate designed for prismatic $\mathrm{L}\mathrm{i}\mathrm{M}{\mathrm{n}}_2{\mathrm{O}}_4$/graphite cells under a demanding 5 C discharge. A systematic parametric investigation is conducted to quantify the effects of ambient temperature (293–343 K), microchannel number (2–6), and coolant inlet velocity (0.1–0.6 m/s) on the maximum battery temperature (${\mathrm{T}}_{\mathrm{m}\mathrm{a}\mathrm{x}}$) and temperature difference ($\mathsf{\Delta }\mathrm{T}$). Results demonstrate that the proposed system exhibits exceptional environmental robustness: over a 50 K ambient temperature span, ${\mathrm{T}}_{\mathrm{m}\mathrm{a}\mathrm{x}}$ increases by merely 2.0 K, remaining safely below the 323 K industry limit. Densifying the channel count from 2 to 6 further reduces ${\mathrm{T}}_{\mathrm{m}\mathrm{a}\mathrm{x}}$ by 1.55 K and narrows $\mathsf{\Delta }\mathrm{T}$ to 4.25 K, successfully satisfying the strict 5 K temperature uniformity standard. Furthermore, the thermal benefit of elevating inlet velocity exhibits a pronounced diminishing-return trend governed by the asymptotic reduction in bulk coolant temperature rise, dictating a critical trade-off against the quadratically escalating pumping power. Ultimately, these findings provide robust theoretical guidelines for the rational design of safe and energy-efficient battery thermal management systems. Full article

Nuclear energy has emerged as a crucial technological solution for ensuring energy security and achieving carbon neutrality goals, given its ultra-high energy density and near-zero carbon emissions against the backdrop of rapid socioeconomic development, increasing energy demands, and accelerated global transition toward low-carbon energy structures. As the core component for energy conversion in nuclear reactors, fuel elements critically determine reactor efficiency and safety performance, with the fission product retention capability of silicon carbide layers in multilayer-coated fuel particles having been thoroughly validated through high-temperature gas-cooled reactor irradiation tests. The precise sphericity control of large-sized UO₂ fuel kernels represents a fundamental requirement for enhancing tristructural isotropic (TRISO) fuel particle performance and advancing Generation IV nuclear power plant development. This study presents a sphericity control strategy based on sol–gel processing that synergistically integrates physicochemical regulation of gelling media with multi-field washing flow field optimization. By implementing silicone oil-mediated interfacial tension gradient control, we effectively suppressed gel sphere destabilization while developing an innovative three-phase sequential washing technique involving kerosene washing, anhydrous ethanol interfacial transition, and ammonia solution replacement, which significantly enhanced mass transfer diffusion in stagnant liquid films and revolutionized fuel microsphere washing technology with improved efficiency and quality. Experimental results demonstrate that this integrated approach increases kernel sphericity qualification to 99.8%, reduces washing solution consumption by 79%, and achieves an average sphericity of 1.03. The research establishes a coupling mechanism between gelling media and multi-field washing processes, elucidating the synergistic effect between interfacial tension regulation and washing optimization, thereby providing both theoretical foundations and engineering application basis for the precision manufacturing of high-performance nuclear fuels. Full article

Aluminum–graphene nanoplatelet (Al/GNP) composites have attracted significant attention as lightweight structural materials, yet their mechanical performance is strongly influenced by interfacial reactions and the formation of carbides. In this study, Al/GNP composites containing 0.1–1.1 wt.% graphene were produced via powder metallurgy and hot extrusion at 400 °C and 500 °C. Hot extrusion at the higher temperature enables the controlled in situ formation of aluminum carbide (Al₄C₃). A comprehensive microstructural characterization using SEM and HRTEM was combined with tensile testing to elucidate the influence of carbide size on mechanical behavior. Hot extrusion at 500 °C promotes the formation of uniformly distributed, nanoscale Al₄C₃ carbides whose size, morphology, and aspect ratio depend on graphene content. Composites containing nano-sized carbides exhibit a markedly improved strength–ductility balance compared to carbide-free counterparts, with optimal performance achieved at 0.3 and 0.7 wt.% GNPs. The enhancement is attributed to synergistic strengthening mechanisms involving improved interfacial bonding, efficient load transfer, nanoscale dispersion strengthening, and carbide–dislocation interactions. The results indicate that the controlled formation of nanoscale Al₄C₃ is not detrimental; rather, it contributes to the optimization of the mechanical properties of Al/GNP composites. Unlike most previous studies that treat carbide formation as a detrimental effect, this work demonstrates that its controlled nanoscale evolution can be used as a deliberate strengthening strategy through its influence on microstructural mechanisms. Full article

To address the inherent low voltage and poor energy density of LiFePO₄, LiFe_0.6Mn_0.4PO₄ (LFMP) has emerged as a promising cathode for next-generation lithium-ion batteries. However, its practical application is severely hindered by intrinsic limitations such as low electronic conductivity and sluggish Li⁺ diffusion. To address these challenges, this study investigates the effects of silver (Ag) doping on the structural and electrochemical performance of LFMP. Through a facile high-temperature solid-state approach, Ag⁺ ions are successfully incorporated into the LFMP matrix, and the resulting material (LFMP-Ag) is systematically characterized. The results reveal that partial Ag is doped into the LFMP lattice while an Ag-rich secondary phase within LFMP particles is detected, significantly enhancing the charge transfer kinetics. The Ag-doped LFMP cathodes exhibit superior discharge capacity of 142.1 mAh g⁻¹ at 0.1 C, enhanced rate capability, better cyclic stability (92.3% retention after 300 cycles) and enhanced thermal stability, surpassing the undoped LFMP counterparts. These findings demonstrate that Ag doping is an effective strategy for optimizing the electrochemical performance of LFMP cathodes, offering a viable pathway toward advanced battery technologies. Full article

Improving the energy efficiency of historic field stone masonry buildings often requires internal insulation, as external insulation is frequently restricted by heritage and architectural constraints. Internal insulation, however, alters the hygrothermal behavior of massive masonry walls and may increase moisture-related risks. This study assesses the hygrothermal performance of an internally insulated historic field stone masonry wall under past and projected future climatic conditions using long-term transient simulations. Coupled heat and moisture transfer simulations were performed with the DELPHIN software for an uninsulated reference wall and an internally insulated configuration. The analyses accounted for wind-driven rain, masonry heterogeneity, and variations in inner core composition. Past conditions were represented by a continuous 20-year measured climate dataset, while future conditions were evaluated using regional late-century climate projections (RCP2.6 and RCP8.5). Hygrothermal performance was evaluated based on moisture mass density, freeze–thaw exposure, and mold-relevant temperature–relative humidity conditions at predefined evaluation points within the wall. The results show that moisture accumulation develops gradually and cannot be reliably captured by short simulation periods. Internal insulation redistributes moisture-related risks within the wall rather than fundamentally altering the seasonal moisture regime. Freeze–thaw exposure occurs under all investigated climates, while mold-relevant humidity conditions persist at interior-adjacent locations. The findings demonstrate the importance of multi-year hygrothermal analyses when assessing moisture-related risks in internally insulated historic masonry walls. Full article

A 0.3 V nanowatt CCII⁻ is presented in 0.18 $\mathsf{\mu }$m TSMC CMOS, targeting ultra-low-power current-mode interfaces. Post-layout extracted simulations demonstrate correct conveying operation with a total DC power consumption of less than 2.40 nW. The low-frequency tracking factors evaluated at 1 Hz are ${\beta }_0=0.9452$ (−0.48 dB) and ${\alpha }_0=0.9609$ (≈−0.35 dB), with $-3$ dB bandwidths of 22.95 kHz and 63.95 kHz for the voltage and current transfers, respectively. Small-signal extraction confirms the intended impedance profile, yielding $R_X=46.73$ M$\mathsf{\Omega }$, $R_Z=1.204$ G$\mathsf{\Omega }$, and a very high input resistance $R_Y=392$ G$\mathsf{\Omega }$. Robustness is verified through full PVT and mismatch analyses, showing stable functionality across process corners, a 0–80 °C temperature range, and 270–330 mV supply variations while maintaining nanowatt-level dissipation. Full article