Search Results (994)

The constitutive model is widely employed to characterize the rheological properties of metallic materials under high-temperature conditions. It is typically derived from a series of high-temperature tests conducted at varying deformation temperatures, strain rates, and strains, including hot stretching, hot compression, separated Hopkinson pressure bar testing, and hot torsion. The original experimental data used for establishing the constitutive model serves as the foundation for developing phenomenological models such as Arrhenius and Johnson–Cook models, as well as physical-based models like Zerilli–Armstrong or machine learning-based constitutive models. The resulting constitutive equations are integrated into finite element analysis software such as Abaqus, Ansys, and Deform to create custom programs that predict the distributions of stress, strain rate, and temperature in materials during processes such as cutting, stamping, forging, and others. By adhering to these methodologies, we can optimize parameters related to metal processing technology; this helps to prevent forming defects while minimizing the waste of consumables and reducing costs. This study provides a comprehensive overview of commonly utilized experimental equipment and methods for developing constitutive models. It discusses various types of constitutive models along with their modifications and applications. Additionally, it reviews recent research advancements in this field while anticipating future trends concerning the development of constitutive models for high-temperature deformation processes involving metallic materials. Full article

The current study explores the changes in beef quality following partial freezing and during superchilled storage, alongside chilled storage comparisons. Kinetic models were developed to predict changes in colour difference (∆E), thiobarbituric acid−reactive substances (TBARS), total volatile basic nitrogen (TVB−N), drip loss and firmness. Beef samples were partially frozen in an air blast freezer at −30 °C for 9 min prior to storage at −5 °C, −4 °C, −2.8 °C, −1.8 °C. Chilled beef samples were directly stored at 2 °C and 6 °C without partial freezing. All samples were stored for 21 days. The lightness (L*), redness (a*), yellowness (b*) and colour difference (∆E) were significantly lower in superchilled storage samples compared to chilled storage samples. The pH of beef samples increased gradually over time (p < 0.05). TBARS, TVB−N and drip loss increased while firmness decreased with the increase in storage time in both storage conditions (p < 0.05). Overall, beef quality was affected by both storage duration and temperature. Firmness followed the first order kinetic model; drip loss, TVB−N, TBARS and colour difference (∆E) fitted the zero−order kinetic model. Temperature dependence was adequately modelled using Arrhenius−type equation with the activation energy values of 110.111, 52.870, 68.553, 119.480, 47.301 kJ/mol for drip loss, firmness, TBARS, TVB−N and colour difference (∆E), respectively. The models demonstrated strong predictive performance, with RMSE and MAPE values within ±10%. The developed kinetic models successfully predicted quality changes within the −5 °C to 6 °C temperature range. Full article

An analytical study of the interaction of an ideal gas flow with a detonation wave was performed with account for the activation energy of chemical processes. Based on the modified Rankine-Hugoniot conditions, the effect of heat release on the limiting characteristics of detonation was analyzed. A dependence of the limiting value of the exponent Arrhenius number on the Mach number before the shock wave has been obtained. As the Mach number increases, the limiting value of the Arrhenius number decreases. An equation has been derived for determining the limiting value of the compression ratio in the shock wave. The effect of heat release intensity on the limiting compression ratio in a shock wave was elucidated. Also studied were effects of the Mach number and the Arrhenius number on the limiting compression ratio in a detonation wave. A condition for determining the critical value of the Arrhenius number necessary for the onset of detonation was obtained. Effects of the Mach number and the exponent of the Arrhenius number ${\mathrm{Ar}}_E$ on the critical value of the amplitude Arrhenius number ${\mathrm{Ar}}_A$ were discussed. The symmetry analysis of the gas flow parameters when passing through a detonation wave was performed. Full article

Ethanol upgrading via catalytic C–C coupling, commonly known as the Guerbet reaction, offers a sustainable route to produce 1-butanol, a high-performance biofuel. To address gaps in the mechanistic understanding of the catalytic reaction, we investigated the process involving a fixed-bed reactor, operated at 275–325 °C, 21 bar, and weight hourly space velocities of 0.25–2.5 g_EtOH/(g_cat·h), using helium as a carrier gas, with a 5:1 He/EtOH molar ratio. The catalyst was a MgO–Al₂O₃ mixed oxide (Mg/Al = 2:1), derived from a hydrotalcite precursor. A detailed kinetic model was developed, encompassing 15 species and 27 reversible steps (10 sorption and 17 reaction steps), within a 1+1D sorption–reaction–transport framework. Four C₄-forming pathways were included: aldol condensation to form crotonaldehyde, semi-direct coupling to form butyraldehyde and crotyl alcohol, and direct coupling to form 1-butanol. To avoid overfitting, Arrhenius parameters were grouped by reaction type, resulting in sixty rate parameters and one active site-specific density parameter. The optimized model achieved high accuracy, with an average prediction error of 1.44 times the experimental standard deviation. The mechanistic analysis revealed aldol condensation as the dominant pathway below 335 °C, with semi-direct coupling to crotyl alcohol prevailing above 340 °C. The resulting model provides a robust framework for understanding and predicting complex reaction networks in ethanol upgrading systems. Full article

Hydrogen, as the smallest atom and a key component of water, can penetrate minerals in various forms (e.g., atoms, molecules), significantly influencing their properties. The hydrogen diffusion behavior in corundum (α-Al₂O₃) under high pressure was systematically investigated using the DFT + NEB method. The results indicate that H atoms tend to aggregate into H₂ molecules within corundum under both ambient and high-pressure conditions. However, hydrogen predominantly migrates in its atomic form (H) under both low- and high-pressure environments. The energy barriers for H and H₂ diffusion increase with pressure, and hydrogen diffusion weakens the chemical bonds nearby. Using the Arrhenius equation, we calculated the diffusion coefficient of H in corundum, which increases with temperature but decreases with pressure. On geological time scales, hydrogen diffusion is relatively slow, potentially resulting in a heterogeneous distribution of water in the lower mantle. These findings provide novel insights into hydrogen diffusion mechanisms in corundum under extreme conditions, with significant implications for hydrogen behavior in mantle minerals at high pressures. Full article

Fast charging accelerates lithium-ion battery operation but increases the risk of lithium (Li) plating—a process that undermines efficiency, longevity, and safety. Here, we introduce a predictive modeling framework that captures the onset and severity of Li plating under practical fast-charging conditions. By integrating an empirically parameterized SOC threshold model with time-dependent kinetic simulations and Arrhenius based thermal analysis, we delineate operating regimes prone to irreversible Li accumulation. The framework distinguishes reversible and irreversible plating fractions, quantifies energy losses, and identifies a critical activation energy (0.25 eV) associated with surface-limited deposition. Visualizations in the form of severity maps and voltage-zone risk classifications enable direct application to battery management systems. This approach bridges electrochemical degradation modeling with real-time charge protocol design, offering a practical tool for safe, high-performance battery operation. Full article

The escalating demand for efficient thermal management in lithium-ion batteries necessitates precise characterization of their thermal behavior under diverse operating conditions. This study develops a three-dimensional (3D) electrochemical–thermal coupling model grounded in porous electrode theory and energy conservation principles. The model solves multi-physics equations such as Fick’s law, Ohm’s law, and the Butler–Volmer equation, to resolve coupled electrochemical and thermal dynamics, with temperature-dependent parameters calibrated via the Arrhenius equation. Simulations under varying discharge rates reveal that high-rate discharges exacerbate internal heat accumulation. Low ambient temperatures amplify polarization effects. Forced convection cooling reduces surface temperatures but exacerbates core-to-surface thermal gradients. Structural optimization strategies demonstrate that enhancing through-thickness thermal conductivity reduces temperature differences. These findings underscore the necessity of balancing energy density and thermal management in lithium-ion battery design, proposing actionable insights such as preheating protocols for low-temperature operation, optimized cooling systems for high-rate scenarios, and material-level enhancements for improved thermal uniformity. Full article

To address the issue of coating accumulation model failure in unstable environments, this paper proposes a dynamic control method based on visual differential feedback. An image difference model is constructed through online image data modeling and real-time reference image feedback, enabling real-time correction of the coating accumulation model. Firstly, by combining the Arrhenius equation and the Hagen–Poiseuille equation, it is demonstrated that pressure regulation and temperature changes are equivalent under dataset establishment conditions, thereby reducing data collection costs. Secondly, online paint mist image acquisition and processing technology enables real-time modeling, overcoming the limitations of traditional offline methods. This approach reduces modeling time to less than 4 min, enhancing real-time parameter adjustability. Thirdly, an image difference model employing a CNN + MLP structure, combined with feature fusion and optimization strategies, achieved high prediction accuracy: R² > 0.999, RMSE < 0.79 kPa, and σ_e < 0.74 kPa on the test set for paint A; and R² > 0.997, RMSE < 0.67 kPa, and σ_e < 0.66 kPa on the test set for aviation paint B. The results show that the model can achieve good dynamic regulation for both types of typical aviation paint used in the experiment: high-viscosity polyurethane enamel (paint A, viscosity 22 s at 25 °C) and epoxy polyamide primer (paint B, viscosity 18 s at 25 °C). In summary, the image difference model can achieve dynamic regulation of the coating accumulation model in unstable environments, ensuring the stability of the coating accumulation model. This technology can be widely applied in industrial spraying scenarios with high requirements for coating uniformity and stability, especially in occasions with significant fluctuations in environmental parameters or complex process conditions, and has important engineering application value. Full article

Addressing the urgent need for lightweight and reusable energy-absorbing materials in aviation impact resistance, this study introduces an innovative multi-directional braided metamaterial design enabled by 4D printing technology. This approach overcomes the dual challenges of intricate manufacturing processes and the limited functionality inherent to traditional textile preforms. Six distinct braided structural units (types 1–6) were devised based on periodic trigonometric functions (Y = A sin(12πX)), and integrated with shape memory polylactic acid (SMP-PLA), thereby achieving a synergistic combination of topological architecture and adaptive response characteristics. Compression tests reveal that reducing strip density to 50–25% (as in types 1–3) markedly enhances energy absorption performance, achieving a maximum specific energy absorption of 3.3 J/g. Three-point bending tests further demonstrate that the yarn amplitude parameter A is inversely correlated with load-bearing capacity; for instance, the type 1 structure (A = 3) withstands a maximum load stress of 8 MPa, representing a 100% increase compared to the type 2 structure (A = 4.5). A multi-branch viscoelastic constitutive model elucidates the temperature-dependent stress relaxation behavior during the glass–rubber phase transition and clarifies the relaxation time conversion mechanism governed by the Williams–Landel–Ferry (WLF) and Arrhenius equations. Experimental results further confirm the shape memory effect, with the type 3 structure fully recovering its original shape within 3 s under thermal stimulation at 80 °C, thus addressing the non-reusability issue of conventional energy-absorbing structures. This work establishes a new paradigm for the design of impact-resistant aviation components, particularly in the context of anti-collision structures and reusable energy absorption systems for eVTOL aircraft. Future research should further investigate the regulation of multi-stimulus response behaviors and microstructural optimization to advance the engineering application of smart textile metamaterials in aviation protection systems. Full article

Epoxy adhesives derived from bisphenol A diglycidyl ether (BADGE) are widely utilized in segmental construction—particularly in precast concrete structures—and in building structural strengthening, owing to their outstanding adhesion properties and long-term durability. These materials constitute a significant class of polymeric adhesives in structural engineering applications. However, BADGE-based epoxy adhesives are susceptible to aging under service conditions, primarily due to environmental stressors such as thermal cycling, oxygen exposure, moisture ingress, ultraviolet radiation, and interaction with corrosive media. These aging processes lead to irreversible physicochemical changes, manifested as degradation of microstructure, mechanical properties, and dynamic mechanical properties to varying degrees, with performance deterioration becoming increasingly significant over time. Notably, for the mechanical properties of concern, the decline can exceed 40% in accelerated aging tests. A comprehensive understanding of the aging behavior of BADGE-based epoxy resin under realistic environmental conditions is essential for predicting long-term performance and ensuring structural safety. This paper provides a critical review of existing studies on the aging behavior of BADGE-based epoxy resins. This paper summarizes the findings of various aging tests involving different influencing factors, identifies the main degradation mechanisms, and evaluates current methods for predicting long-term durability (such as the Arrhenius method, Eyring model, etc.). Furthermore, this review provides recommendations for future research, including investigating multifactorial aging, conducting natural exposure tests, and establishing correlations between laboratory-based accelerated aging and field-exposed conditions. These recommendations aim to advance the understanding of long-term aging mechanisms and enhance the reliability of BADGE-based epoxy resins in structural applications. Full article

Background/Objectives: Denture hygiene is essential for the prevention of oral candidiasis, a condition frequently associated with Candida albicans colonization on denture surfaces. Cetylpyridinium chloride (CPC)-loaded montmorillonite (CPC-Mont) has demonstrated antimicrobial efficacy in tissue conditioners and demonstrates potential for use in antimicrobial coatings. In this study, we aimed to develop and characterize CPC-Mont-containing coating films for dentures, focusing on their physicochemical behaviors and antifungal efficacies. Methods: CPC was intercalated into sodium-type montmorillonite to prepare CPC-Mont; thereafter, films containing CPC-Mont were fabricated using emulsions of different polymer types (nonionic, cationic, and anionic). CPC loading, release, and recharging behaviors were assessed at various temperatures, and activation energies were calculated using Arrhenius plots. Antimicrobial efficacy against Candida albicans was evaluated for each film using standard microbial assays. Results: X-ray diffraction analysis confirmed the expansion of montmorillonite interlayer spacing by approximately 3 nm upon CPC loading. CPC-Mont showed temperature-dependent release and recharging behavior, with higher temperatures enhancing its performance. The activation energy for CPC release was 38 kJ/mol, while that for recharging was 26 kJ/mol. Nonionic emulsions supported uniform CPC-Mont dispersion and successful film formation, while cationic and anionic emulsions did not. CPC-Mont-containing coatings maintained antimicrobial activity against Candida albicans on dentures. Conclusions: CPC-Mont can be effectively incorporated into nonionic emulsion-based films to create antimicrobial coatings for denture applications. The films exhibited temperature-responsive, reversible CPC release and recharging behaviors, while maintaining antifungal efficacy, findings which suggest the potential utility of CPC-Mont-containing films as a practical strategy to prevent denture-related candidiasis. Full article

The kinetics of the depolymerization of natural rubber (NR) to hydroxyl-terminated natural rubber (HTNR) by hydrogen peroxide (H₂O₂) in the presence of a Fenton catalyst within an acidic milieu and under ultraviolet radiation has been rigorously examined utilizing infrared spectroscopy to determine the alterations in molar mass and the functional characteristics. The kinetic model was analyzed in accordance with the elementary reaction, encompassing the following mechanisms: the interaction between hydroxyl radicals and NR, producing radical NR and hydroxylated NR; the reaction wherein radical NR and hydroxyl radicals yield hydroxylated NR; and the subsequent reaction of hydroxylated NR with hydroxyl radicals producing lower radical NR, hydroxylated terminated NR, radical NR, and hydroxylated NR. The conversion of the NR polymer and the total hydroxyl content were discerned at the absorption bands of the CH₂-CH₂ and OH groups located at 850 cm⁻¹ and 3400 cm⁻¹, respectively. The absorption peak at 1850 cm⁻¹ attributed to CH₃ was employed as the reference group for calibration. The influence of the temperature on the depolymerization process conformed to the Arrhenius equation, characterized by activation energies of 750 K and 1200 K. The impact of the H₂O₂/Fenton ratio on the depolymerization process follows a power law with power coefficients of 1.97 and 1.82. Full article

To quantitatively describe the frequency domain spectroscopy (FDS) characteristics of transformer oil-paper insulation under varying temperature, moisture, and aging conditions, a modified Cole–Cole model is introduced. This model decomposes the dielectric spectrum into polarization, DC conduction, and hopping conduction components, with parameters reflecting insulation characteristics. Methods for determining initial parameter values and optimizing the objective function are proposed. Using a three-electrode setup, FDS measurements were conducted on oil-paper insulation samples at different temperatures, and extracted parameters were analyzed for their variation patterns. Within the frequency range of 1.98 × 10⁻⁴ Hz to 1 × 10³ Hz, the model achieves a goodness-of-fit (R²) exceeding 0.97 for both real and imaginary permittivity components, with the sum of squared errors reduced from 259 to 57.35 at 70 °C, outperforming the fundamental Cole–Cole and Ekanayake’s models. Temperature significantly affects the relaxation and DC conductivity components; both adhere to the Arrhenius equation, enabling precise condition assessment of transformer insulation. Full article

To investigate the aging behavior of HTPB composite solid propellant under constant strain conditions, this study analyzed the aging patterns of the propellant’s maximum elongation at four temperatures (323.15 K–343.15 K) and five strain levels (0–18%) using thermal–mechanical coupled accelerated aging tests. The results show that the maximum elongation initially increases, then decreases under constant strain conditions. To measure the mechanical work-induced decrease in the activation motor, we created a modified Arrhenius model with a strain correction factor based on empirical observations. The acceleration coefficient of a solid motor grain at the accelerated aging temperature (323.15 K) in comparison to the long-term storage temperature (293.15 K) was found to be 20.08 through finite element analysis. This means 206.80 days at the accelerated aging temperature is equivalent to 10 years at the long-term storage temperature. Full article

The aim of this work is to investigate the effect of curing temperature and time on the development of compressive strength in geopolymer mortars produced using ground granulated blast-furnace slag (GGBFS) and fly ash (FA). Considering curing circumstances, both the activation energy and the reference temperature could be used properly to build a reliable anticipated model for predicting the compressive strength of geopolymer-based products (mortar and concrete) using maturity-based techniques. In this study, the compressive strength development of geopolymer mortar made from (FA) and (GGBFS) under varying curing conditions. The mortar was prepared using an alkali solution of sodium hydroxide (NaOH) and sodium silicate (Na₂SiO₃) in a 1:1 ratio, with NaOH molarity of 12. Specimens were cast following ASTM C109 standards, with a binder/sand ratio of 1:2.75, and compacted for full densification. FA-based mortar was cured at 40 °C, 80 °C, and 120 °C, while GGBFS-based mortar was cured at 5 °C, 15 °C, and 40 °C for durations of 0.5 to 32 days. Compressive strength was evaluated at each curing period, and data were analyzed using ASTM C1074 procedures alongside a computational model to determine the best-fit datum temperature and activation energy. The Nurse-Saul maturity method and Arrhenius equation were applied to estimate the equivalent age and maturity index of each mix. A predictive model was developed for geopolymer concrete prepared at an alkali-to-binder ratio of 0.45 and NaOH molarity of 12. The final equation demonstrated high accuracy, offering a reliable tool for predicting geopolymer strength under diverse curing conditions and providing valuable insights for optimizing geopolymer concrete formulations. Full article