Search Results (365)

Aiming at the challenging issue of nonlinear coupling control between cooling intensity and solidification rate in the secondary cooling zone of round billet continuous casting, this study proposes an efficient 3D temperature field modeling method that integrates hybrid coordinate systems with equal-area meshing. The model is applicable to the temperature range of 800–1520 °C during the continuous casting process. With the modeling strategies of constructing an r-θ-z hybrid coordinate system and designing a dynamic equal-area meshing method, and combined with a topological structure optimization algorithm, the geometric adaptability and numerical stability of the model are significantly improved. Based on this, an explicit-semi-implicit dual-mode finite difference solution model is developed, where the explicit scheme meets real-time online calculation requirements, and the semi-implicit scheme combined with preconditioned Gauss–Seidel iteration enables high-precision offline simulation. Furthermore, a boundary condition model incorporating adaptive mold heat flux correction and multi-mechanism heat transfer in the secondary cooling zone is established. Based on Microsoft Visual Studio 2019 (Version 16.11) C++ development, SIMD vectorization and temperature gradient threshold optimization technologies are employed, resulting in a 35% improvement in computational efficiency. Industrial validation results show that, taking 42CrMo steel with a casting speed of 0.24 m/min and a cross-section of φ600 mm as an example, the deviation between the calculated surface temperature (887 °C) and the measured value (876 °C) of the round billet in the straightening zone is only 11 °C, and the calculation error of the cold billet diameter is only 0.325% (with a calculated value of 597.548 mm and a measured average value of 599.5 mm), both meeting the accuracy requirements for engineering applications. The model breaks through the limitations of traditional empirical formulas and provides theoretical support for digital control of continuous casting processes and quality optimization of high-alloy steels. Full article

Plant diversity is a key indicator of ecosystem structure, function, and restoration status, yet its rapid assessment remains challenging in sandy ecosystems where vegetation is sparse, spatially heterogeneous, and strongly affected by exposed soil backgrounds. In such environments, conventional greenness-based spectral indices may not adequately capture species-level variation because plant communities are controlled not only by photosynthetic biomass but also by soil moisture, micro-topography, and dune-related habitat heterogeneity. This study evaluated the potential of Sentinel-2-derived spectral indices for estimating plant α-diversity in the Hunshandak Sandland, northern China. Based on field observations from 888 plots collected during 2017–2024, four α-diversity metrics—species richness, Shannon–Wiener index, Simpson index, and Pielou evenness index—were calculated and compared with 21 spectral indices using correlation analysis, partial least squares regression (PLSR), and random forest (RF) models. The results showed that model performance varied substantially among diversity metrics. Species richness was estimated with the highest accuracy, whereas Shannon–Wiener, Simpson, and Pielou indices showed weaker predictability, indicating that remotely sensed spectral indices were more sensitive to species number than to abundance distribution and evenness. Moisture- and soil-background-sensitive indices, including the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Bare Soil Index (BSI/BRI), and Chlorophyll Absorption Ratio Index (CARI), showed relatively stable relationships with plant diversity across different vegetation gradients. Although the overall explanatory power was moderate rather than high, the results demonstrate the practical value of Sentinel-2 spectral indices for regional screening of plant diversity patterns in sandy ecosystems. This study provides empirical evidence for biodiversity monitoring and ecological restoration assessment in semi-arid sandy landscapes and highlights the need to integrate environmental covariates, multi-source remote sensing, and phenological information in future studies. Full article

This work investigates the behavior of carbon dioxide (CO₂) near the surface of different single-atom alloys to evaluate their potential as catalysts for decarbonization processes. Specifically, 26 transition metals from the first three transition series, alloyed with three low Miller index copper supports, were considered. Adsorption energies and distances of linear CO₂, trigonal CO₂, and CO* + O* on the surfaces were calculated using the semiempirical computational method MOPAC-PM7. Additionally, activation energies were determined from previously published research. The proposed methodology is less computationally demanding than DFT studies, and results show good agreement with both experimental and simulated data. This approach provides a computationally efficient methodology for screening promising materials that convert CO₂ into valuable products, such as methane and methanol. Full article

In the present work, the elastic modulus of several types of polymer nanocomposites has been analyzed with a semiempirical model which takes into consideration agglomerate formation and their impact on the nanocomposites’ mechanical performance. The nanocomposites under investigation were either hybrids with a combination of graphene oxide (GO) with multi-walled carbon nanotubes (MWCNTs) or carbon nanofibers (CNFs) at various loadings, or monofillers with varying nanoparticle sizes, at a constant nanofiller loading. In addition, the effect of the type of polymeric matrix on the same nanofiller combinations has been examined. The basic assumption of two phases, namely a matrix with finely dispersed nanoparticles coexisting with agglomerates, was analyzed. The elastic stiffness of the first phase was calculated by the Mori–Tanaka model, and hereafter a semiempirical model was utilized for the estimation of the agglomerates’ stiffness. Within the context of this model, it was shown that the agglomerates’ volume fraction, combined with the nanoparticles’ density, namely the nanoparticles’ volume fraction in the agglomerates and consequently the inclusions’/agglomerates’ enhanced modulus, may cause a substantial improvement in the Young’s modulus, which cannot be explained by conventional mechanical models. These results apply to both nanocomposite types, hybrids at various nanofiller loadings and monofillers with varying particle sizes. Full article

The solubility values of polyphenolic compounds in different extraction solvents are crucial for their recovery from natural matrices. Hansen solubility parameters (HSPs) stand out as a predictive tool for evaluating solute-solvent affinity and thus rational solvent selection for extraction processes. In this study, HSPs of trans-resveratrol and hesperetin were calculated using a semi-empirical method to assess the capability to predict the solubility behavior of both polyphenols in organic binary solvent mixtures. Experimental solubility of both polyphenols was determined in up to 21 monosolvents at 298.15 K and 0.1 MPa and used to classify them to iteratively calculate HSPs. Calculated HSPs were compared and discussed with literature values in terms of molecular interactions, demonstrating a fair agreement. Solubility of trans-resveratrol and hesperetin was then determined in methanol + MEK, ethanol + MEK, methanol + MiBK, ethanol + MiBK, and methanol + ethanol binary solvent mixtures. trans-Resveratrol achieved higher mole fraction solubility than hesperetin in all binary mixtures across the whole molar fraction range except in methanol + MiBK. Both compounds exhibited enhanced solubility in all alcohols + ketone binary mixtures, attributed to synergistic solvent effects. HSP analysis revealed a minimum Hansen distance between solute and solvent mixtures at compositions corresponding to the solubility maximum in synergistic systems. Additionally, calculated HSPs proved to effectively estimate the concentration at which this phenomenon occurs in all tested systems, reaching a robust correlation between maximum solubility and minimum Hansen distance. Overall, insights from this study underscore the effectiveness of experimentally derived HSPs in predicting the solubility behavior of polyphenols and seek to provide valuable guidance on solvent selection strategies for the recovery of bioactive compounds. Full article

Traditional villages in the Jiangnan region have experienced significant spatial transformation under rural revitalization, yet thermal environment regulation in public spaces remains insufficiently addressed. This study examines how spatial morphology influences microclimate and outdoor thermal comfort during summer and proposes evidence-based climate-responsive strategies. Three representative provincial-level traditional villages in Wuxi—Yaogeli Village, Zhu Village, and Huangtutang Ancient Village Area—were selected as case studies. Public spaces were classified into open, semi-open, and semi-private types according to spatial openness. Field microclimate measurements and thermal comfort surveys were conducted, and Physiological Equivalent Temperature (PET) was calculated to evaluate thermal conditions. Results show that rural public spaces generally experience significant summer heat stress, with PET exceeding the neutral range during most daytime periods. Spatial openness is significantly positively correlated with PET, identifying solar radiation as the dominant thermal driver. Water bodies provide cooling benefits within limited spatial ranges, constrained by configuration and ventilation conditions. Ecological and composite surfaces reduce heat accumulation compared to single materials. These findings indicate that thermal comfort in rural public spaces is a multi-factor and interaction-driven process, providing empirical support for climate-adaptive rural renewal. Full article

This paper presents the synthesis, physicochemical characterisation, and analytical applications of chemiluminescent (CL) labels based on acridinium salts (ALs) for biomedical diagnostics. These compounds emit light as a result of oxidative reactions and represent an established class of reagents widely employed in chemiluminescence immunochemical assays (CLIAs) today. A series of structurally differentiated acridinium labels (AL1–AL5) was synthesised applying mostly original synthetic routes and purified to chromatographic purity (>90%, RP-HPLC). The compounds, including a commercial product treated as a reference, were successfully conjugated to anti-human IgG, yielding stable immunochemical reagents suitable for immunoassays with CL detection. The chemiluminescence properties of the obtained labels and their protein conjugates were investigated in aqueous buffers and in the presence of surfactants. The emission profiles exhibited characteristic flash-type kinetics with emission maxima occurring within 0.15–0.25 s after reaction initiation. The presence of surfactants more or less significantly enhanced the emission intensity, with signal increases of up to approx. 2-fold compared to surfactant-free systems. Analytical calibration demonstrated a linear response of signal derived from native labels over at least one order of magnitude of concentration, with detection limits falling in the range of 10⁻⁹–10⁻¹⁰ M, confirming the high sensitivity of the developed compounds. The experimental results were supported by theoretical studies using density functional theory (DFT), which confirmed the energetic feasibility of the CL reaction pathway and identified structural factors influencing activation barriers. Additional semiempirical calculations (PM7) indicated that the dielectric environment and proximity of ionic species can influence the reaction energetics, providing mechanistic support for the experimentally observed effects of surfactants. The results demonstrate that both molecular structure and microenvironment influence CL efficiency and kinetics of the investigated systems. The developed acridinium labels exhibit analytical performance better or comparable to commercial reagents and are fully compatible with standard immunodiagnostic conjugation protocols, confirming their suitability for use in modern chemiluminescent immunoassays. Full article

Arsenic (As) contamination of soils is a critical environmental and geochemical concern, with its mobility and bioavailability largely controlled by molecular-scale interactions with soil minerals. This study investigates the adsorption behavior of arsenate [As(V)] and arsenious acid [As(III)] on major clay minerals to elucidate fundamental controls on As retention in soil and sediment systems. Molecular modeling approaches were employed to investigate these interactions. Density functional theory (DFT) calculations were performed on cluster models of illite, chlorite, montmorillonite, and kaolinite to evaluate adsorption configurations and binding energies of arsenate and arsenious acid. In addition, semiempirical (PM6) and classical force-field (UFF) methods were used to examine the influence of vermicompost-derived organic matter on arsenate-mineral interactions. Multiple adsorption configurations, including atop atom, bridge, three-fold filled, and three-fold hollow sites, were evaluated, and binding energies were calculated with correction for basis set superposition error. The results indicate that three-fold hollow sites are the most favorable, with As(V) binding energies of 60–65 kcal mol⁻¹ on illite, chlorite, and montmorillonite, reaching 75 kcal mol⁻¹ on kaolinite at a surface distance of 2.7 Å. In contrast, As(III) shows weaker and energetically flatter adsorption, with binding energies of 28–54 kcal mol⁻¹ and larger equilibrium distances of 3.2–4.0 Å. Modeling of vermicompost addition suggests a substantial reduction in arsenate binding on most clay minerals, except illite, indicating competitive or disruptive interactions at mineral surfaces. These findings provide quantitative, atomistic insight into mineral- and amendment-specific controls on As stabilization and mobility in soil and sediment systems. Full article

To address issues such as web and bottom plate cracking and insufficient bending capacity in in-service prestressed concrete box girder bridges, this study proposes internal prestressing and section enlargement composite reinforcement. Firstly, taking a bridge of Shenhai Expressway as the background project, the combined reinforcement method is designed and the reinforcement effect is analyzed by MIDAS/Civil. Secondly, through numerical analysis, the influence of the bond shrinkage of self-compacting concrete with different mix ratios on the stress of the web of the original box girder is analyzed, and the interface between the new and old concrete is carried out. The analysis of the loss of the new prestress on the bonding surface of the new and old concrete is carried out by parameters such as the interface planting rate, the interface shear stiffness and the reinforcement structure. Furthermore, the theoretical calculation method of prestress loss rate of new and old concrete bonding interface is obtained. The results show that the flexural capacity of the normal section of the main beam is significantly improved after reinforcement, and the surplus coefficient is 1.18, which meets the requirements of the secondary safety level, and the mid-span deflection is improved by 34.28%, which verifies the effectiveness and feasibility of the combined reinforcement method. When the content of fly ash is 54%, the bond shrinkage strain and shrinkage stress of self-compacting concrete are reduced to the lowest level, which has the least influence on the existing box girder structure. It is suggested that the reinforcement ratio between the new and old concrete interface is 0.6%, and the interface roughness is 0.9 mm, which can increase the shear resistance of the new and old concrete interface and effectively reduce the transfer loss of prestress at the interface. Error analysis shows that the proposed semi-empirical calculation method has high accuracy with a deviation of less than 10%. Full article

The temperature and concentration dependences of viscosity for blast furnace molten iron were theoretically studied in this paper. Afterwards, a series of semi-empirical viscosity prediction models were compared, and several of which that are suitable for blast furnace molten iron were optimized. The Fe-C system was used as the only benchmark during the whole research to quantify the relationship between component content and melt viscosity. Then, the component action coefficient of viscosity was introduced by fitting the previous viscosity results of iron-based melt. In terms of verification, the viscosity of blast furnace molten iron was measured by using an oscillating cup viscometer, and five semi-empirical viscosity models were selected to calculate the viscosity based on the corresponding concentration of experimental samples. Consequently, by comparing the experimental and calculation results of viscosity, it was concluded that the Hirai model based on the Andrade quasi-crystal theory is the most suitable viscosity prediction model of molten iron in a blast furnace. Full article

Shagamite, KFe₁₁O₁₇ (IMA 2020-091) was discovered in the ferrite zone of gehlenite hornfels from the Hatrurim Complex exposed near Mt. Ye’elim, Hatrurim Basin, Israel. The mineral occurs in outer zones of gehlenite rock blocks that were heterogeneously altered by high-temperature (>1200 °C) ferritization. Ferritization was induced by K-bearing fluids or melts, generated as a by-product of late combustion processes. Shagamite crystallized from a thin melt that formed on the rock surface during cooling to approximately 800–900 °C. It is mainly associated with minerals of the magnetoplumbite group like barioferrite, Sr-analog of barioferrite, and gorerite but also with magnetite, maghemite, harmunite, devilliersite and K(Sr,Ca)Fe₂₃O₃₆ hexaferrite. Shagamite is a modular compound with a β-alumina-type structure (P6₃/mmc, a = 5.9327 (5), c = 23.782 (3) Å, γ = 120°, V = 724.91 (13) ų, Z = 2), and it is isostructural with diaoyudaoite, NaAl₁₁O₁₇, and kahlenbergite, KAl₁₁O₁₇. Its structure is also closely related, though non-isotypic, to those of the magnetoplumbite-group minerals. Shagamite is dark brown with a semi-metallic luster and forms platy crystals flattened on (001). Its mean empirical formula is: (K_1.00Ca_0.15Mn²⁺_0.05Na_0.04Rb_0.01)_Σ1.25(Fe_10.36Mn²⁺_0.15Al_0.14Mg_0.12Zn_0.10Ni_0.07Cu_0.03Cr³⁺_0.02Ti⁴⁺_0.01)_Σ11.00O₁₇. The Vickers microhardness VHN₂₅ = 507 kg/mm² corresponds to a Mohs hardness of ~5. The calculated density, based on the empirical formula and unit-cell parameters, is 4.12 g·cm⁻³. The main bands in the Raman spectrum of shagamite occur at 685 and 715 cm⁻¹ and are assigned to ν₁(FeO₄)⁵⁻ tetrahedral vibrations. Full article

Understanding the impact of climate change on tourism is vital for the economies that rely on it. The tourism sector in Croatia, a country with diverse climatic regions, but also diverse features of tourism, is particularly sensitive to changes in climate variables such as 2 m air temperature and precipitation totals. This study analyzes trends in these two key climate variables from 1961 to 2024 across five representative climatic regions: the-mountainous Lika region (Ličko-senjska County), the Kvarner region on the northern Adriatic coast (Primorsko-goranska County), the Zadar region on the central Adriatic coast (Zadarska Counties), and northern continental Croatia (Varaždinska and Međimurje Counties). Linear trends, 5-year moving averages, and comparisons between two standard climate periods (1961–1990 and 1991–2020) were conducted. Using these data, the monthly self-calibrated Palmer Drought Severity Index (sc-PDSI) and Standardized Precipitation Index (SPI) for seven-time scales were calculated for the period 1961–2024 to assess drought conditions and their implications for tourism across the selected destinations. Frequencies of dry, near normal and wet months, estimated by SPI for a nine-month time scale (SPI-9) and a monthly sc-PDSI, were compared for two subperiods, 1961–1992 and 1993–2024. Meteorological data were contextualized for tourism stakeholders, with a focus on adaptation measures. Semi-structured interviews were conducted with tourism professionals in the study regions, providing qualitative insights into observed changes in climate and tourist behavior, operational challenges, adaptation strategies, level of community engagement, and opportunities envisioned. Objective climatological data were compared with the subjective perceptions of tourism experts using the principle of mixed methods, which allows for triangulation. The climatological data indicated a continuous trend of increasing mean annual air temperatures, as well as anomalies of average precipitation amount. The interviews revealed signals of emerging climate shifts, such as changes in the seasonality of visitors, concerns about water scarcity and heat stress. These findings were interpreted in the context of potential threats and opportunities for the tourism sector, highlighting region-specific adaptation strategies. By combining objective climate data with insights from tourism professionals, this study provides a comprehensive assessment of climate change impacts on tourism and informs for resilient tourism development across Croatia’s diverse regions. This paper presents a methodological framework for developing adaptation recommendations that draw on both empirical climate data and the lived experiences of tourism work practitioners. Full article

Accurate prediction of drilling fluid rheological parameters under high-temperature and high-pressure (HTHP) conditions is critical for reliable drilling hydraulics and wellbore pressure control in deep and ultra-deep wells. However, most existing empirical and semi-empirical rheological models are developed for limited temperature–pressure ranges and specific fluid formulations, which restrict their applicability and accuracy under HTHP conditions. In this study, systematic rheological experiments were conducted on multiple drilling fluid systems over wide temperature–pressure ranges (20–200 °C and 0.1–200 MPa). Based on the experimental data, a unified predictive model for key rheological parameters was developed using a symbolic regression (SR) algorithm. The model performance was evaluated using standard statistical metrics and compared with commonly used conventional models. Compared with conventional models, the proposed model shows stronger applicability for predicting the rheological parameters of the investigated oil-based and water-based drilling fluids over a wider temperature–pressure range. It effectively overcomes the limitations of existing models under HTHP conditions (150–200 °C and 80–200 MPa) and demonstrates improved prediction accuracy and robustness for both high- and low-density drilling fluids. The overall prediction errors are generally within approximately 10%. The results indicate that the proposed unified model provides a reliable and computationally efficient tool for predicting drilling fluid rheological parameters under HTHP conditions, facilitating its integration into wellbore hydraulics, wellbore pressure, and equivalent circulating density calculations in deep and ultra-deep well applications. Full article

A semi-empirical lumped parameter model for the extraction process of traditional Chinese medicine based on thermal equilibrium was established in this work. In this model, the effect of heat dissipation was considered. Differential equations was solved using numerical methods. Key model parameters such as the overall heat transfer coefficient and heat dissipation coefficient were obtained by fitting measured data. In the laboratory scale, Ginkgo biloba leaves were used as the liquid-solid extraction object to systematically investigate the effects of liquid-to-solid ratio, extraction temperature, solvent ratio, and slice particle size on the temperature changes during the extraction process. The average determination coefficient (R²) of the model fitting was 0.9955, and the R² value for the prediction group was 0.9950. In the laboratory scale, extraction experiments of Xiaochaihu Decoction were conducted, and the performance of the model was verified. Furthermore, the model was applied to the mixed decoction process of five medicinal materials (Bupleurum, Glycyrrhiza, Scutellaria, Codonopsis, and Jujube) in industrial-scale for the production of Xiaochaihu capsules. The temperature change curves of three extraction tanks were all fitting well. The fitting results indicated abnormal heat transfer performance in Tank No. 1, providing a prompt for equipment maintenance and process optimization for the enterprise. A feasible method for temperature calculation and abnormal identification in the industrial process of traditional Chinese medicine extraction was provided in this work. Full article

The traditional way to model the statistics of turbulent flow and dispersion is through averaged conservation equations, in which the turbulent transport terms are described by semi-empirical expressions. A new development has been reported by Brouwers in a number of consecutive papers published over the last 15 years. The new development is that presented descriptions can be obtained through the application of fundamental principles of statistical physics and making use of the asymptotic structure of turbulence at a high Reynolds number. They no longer rely on empirical constructions, minimise calibration factors, and are not limited to specific flow situations. This article updates the contents of these works and presents them in coherent manner. The first derivations are presented as expressions for turbulent diffusion. These are subsequently implemented in a closed set of equations expressing the conservation of mean momentum, mean fluctuating energy, and energy dissipation rate. Predictions from these equations are shown to compare favourably with the results of direct numerical simulations (DNS) of the Navier–Stokes equations of highly anisotropic and inhomogeneous channel flow. The presented model equations provide a solid basis to calculate the main statistical parameters of turbulent flow and dispersion in engineering praxis and environmental analysis. Full article