Search Results (19,449)

This study presents a multiscale investigation of cement-based systems modified with silica fume (SF) and fly ash (FA) for self-compacting concrete (SCC). Cement pastes and mortars with replacement levels of 0%, 5%, 10%, and 15% were evaluated for rheological behavior, hydration kinetics, and microstructural evolution using rotational rheometry, semi-adiabatic calorimetry, scanning electron microscopy, and X-ray diffraction. The results show that SF increases plastic viscosity and promotes structural build-up due to its high specific surface area and pozzolanic reactivity, while its influence on yield stress depends on dispersion conditions and superplasticizer efficiency. In contrast, FA reduces both yield stress and viscosity, improving flowability due to its spherical particle shape. Thermal analysis indicates that SF modifies hydration by reducing and slightly delaying the main exothermic peak at higher dosages, whereas FA mainly lowers the peak temperature with limited effect on its timing. Microstructural analysis reveals that SF contributes to a denser, more homogeneous matrix through pore refinement and increased C–S–H formation, whereas FA systems exhibit a more heterogeneous structure with slower early-age development. The results demonstrate a clear relationship between rheology, hydration, and microstructure. The combined use of SF and FA has been shown to be an effective approach to improving the performance and sustainability of SCC. Full article

We present state-of-the-art kinetic theory determination of the neutron abundance available for the Big-Bang nucleosynthesis (BBN). This paper is motivated by the study of the neutron lifespan measured in the laboratory and the unknown strength of weak interactions coupling constant $G_{\mathrm{F}}$ at finite temperature in the primordial Universe. We draw attention to the relevant dependence of $G_{\mathrm{F}}$ on the symmetry breaking Weinberg angle $s_{\mathrm{W}}^2$, which is a free parameter in the standard model of particle physics. We establish how the value of $s_{\mathrm{W}}^2$ by way of $G_{\mathrm{F}}$ modification influences the neutron abundance available for BBN and neutron lifetime. Full article

This study evaluates the 20-year operational performance (2006–2025) of a preseason prediction system for Atlantic hurricane activity developed at North Carolina State University (NCSU) and compares it with forecasts from Colorado State University (CSU), Tropical Storm Risk (TSR), and NOAA. Unlike previous studies based primarily on hindcast experiments, this analysis uses real-time forecasts generated under evolving model configurations, providing a realistic assessment of operational forecast skill. Results show that NCSU April forecasts exhibit lower mean absolute error than other April-issued forecasts and achieve performance comparable to later-issued forecasts from NOAA and CSU, indicating that improved model formulation can partially offset the advantage of later initialization. To identify the sources of forecast improvement, regression and ensemble analyses are conducted. Forecast adjustments between early- and late-season forecasts are primarily explained by changes in tropical North Atlantic sea surface temperature (SST), while ENSO contributes secondarily as forecast uncertainty decreases beyond the spring predictability barrier. These results establish a clear hierarchy of predictors, with Atlantic SST providing the dominant source of preseason predictability. Multi-model ensemble experiments further show that simple averaging does not outperform the best individual models; instead, selective combinations yield the highest skill, with optimal configurations differing between named storm and hurricane predictions, demonstrating that forecast improvement depends on combining complementary information rather than increasing ensemble size. Forecast performance is also shown to be predictand-dependent, with named storm counts more sensitive to late-spring environmental evolution and hurricane counts more strongly constrained by basin-scale thermodynamic conditions. Despite these advances, all models exhibit reduced skill during extreme seasons, reflecting the intrinsic limits of seasonal predictability. Overall, these results demonstrate that preseason hurricane forecast skill is governed by the interaction of forecast timing, model capability, and a hierarchical structure of environmental predictors, providing a unified framework for interpreting differences among forecasting systems and guiding future model development. Full article

The growing use of reclaimed asphalt pavement (RAP) in hot mix asphalt (HMA) is an important practice to achieve more sustainable pavements, as it reduces the consumption and environmental impact of virgin materials. However, aging induces binder stiffening that requires effective rejuvenation to restore overall performance. This study provides a comprehensive comparative analysis of ten chemically different waste oils—waste engine oil (WEO), waste cooking oil (WCO), yellow grease (YG), waste hydraulic oil (WHO) waste electric transformer oil (WETO), slop oil (SO), sludge-derived bio-oil (SDBO), tire pyrolysis oil (TPO), plastic pyrolysis oil (PPO), and algal residue oil (ARO)—as recycled HMA mixture rejuvenators, linking oil composition to binder regeneration and mixture performance. Binder properties were determined by rotational viscosity (RV), dynamic shear rheometer (DSR) and bending beam rheometer (BBR), whereas mixture performance was assessed in terms of Superpave mechanical properties, Hamburg wheel-tracking test (HWTT) for rutting resistance and mixture BBR for low-temperature cracking resistance. Performance grade (PG) evaluations showed that WETO and WEO restored the 50% and 75% RAP binders, respectively, to a grade close to PG 64-16 at the lowest dosages. The Superpave volumetric properties of all restored mixtures were similar to those of the control mixture, denoting corrected mixture balance and compaction level. HWTT results indicated that WETO-recycled mixtures revealed the lowest rut depth at 50% RAP, while WEO-recycled mixtures exhibited the lowest rut depth at 75% RAP after 20000 passes. Additional evidence supporting these results can be found in BBR mixture data, which demonstrated that WETO at 50% RAP and WEO/WETO at 75% RAP showed the most reduction in creep stiffness and improvement in creep rate. The correlation, regression, and PI analyses were in good agreement with the experimental results, where WETO and WEO exhibited the best overall performance at 50% and 75% RAP, respectively. In summary, these results indicate that the performance of waste oil rejuvenator in recycled HMA mixtures is highly dependent on RAP content and point to WETO and WEO as feasible, environmentally friendly options for high-RAP recycled HMA. Full article

High-strength nanofiber yarns exhibit pronounced nonlinear tensile responses arising from their hierarchical fibrous architecture, yet compact constitutive descriptions remain limited. Here, high-strength polyacrylonitrile nanofiber yarns were prepared by post-drawing as-spun yarns above the glass transition temperature, and their aligned, stacked morphology was confirmed by scanning electron microscopy. Monotonic tensile tests at different loading rates were used to quantify the rate-dependent stress–strain response. The tangent modulus derived from the tensile curve varied strongly with strain, confirming clear deviation from linear viscoelasticity. To capture this behavior, two effective models were established: a modified nonlinear three-element model and a structural four-element model incorporating a nonlinear elastic contribution. Closed-form stress–strain expressions were derived for constant strain-rate loading and fitted to experimental data using nonlinear regression. Both models reproduced the measured tensile curves with high accuracy over the investigated loading-rate range, with correlation coefficients close to unity and low fitting errors. The identified parameters were highly consistent between formulations, indicating functional equivalence for the present monotonic tensile dataset. These results provide a compact framework for characterizing and designing hierarchical polymer nanofiber yarns. Full article

Energy pile groups present a dual-functional solution for structural support and geothermal energy utilization, yet their thermo-mechanical interactions with conventional piles remain insufficiently understood. This study establishes a 3D transient finite element model incorporating thermo-hydro-mechanical coupling to investigate thermal interference and differential settlement in hybrid pile groups under seasonal thermal loading. Systematic parametric analyses of pile length (10–30 m), diameter (1–2 m), and spacing (2D–3D) reveal two key findings: (1) Thermal perturbations in adjacent conventional piles exhibit distance-dependent attenuation characteristics, with measurable temperature variations (1–4 °C) observed within 4D spacing distances; (2) Differential settlement patterns demonstrate significant dependence on thermal operation modes, where heating cycles induce upward thermal stresses while cooling enhances consolidation settlement. The numerical framework is validated against field monitoring data and benchmarked with COMSOL 5.6/ABAQUS 6.14 simulations. Through optimized pile arrangements and spacing configurations, we demonstrate effective mitigation strategies for thermal interference and structural deformation, providing key guidance for the design of geothermal-energy-integrated foundation systems. Full article

In some Generation IV reactor configurations, embrittlement of the liquid metal can manifest in various forms, and this behaviour strongly depends on the specific solid–liquid couple. For the ALFRED demonstrator, which will be built at the RATEN ICN site in Romania, the study of embrittlement induced by molten lead in 316L stainless steel at temperatures of 350–450 °C is of interest. The purpose of the paper is to evaluate the effect of liquid metal embrittlement on the fracture mechanics properties of 316L tested in liquid lead. To do this, the “Normalisation Data Reduction Technique” (ASTM E1820) is used to obtain the J-R resistance curve for 316L steel in molten lead. In this way, the fracture mechanics parameters were obtained, indicating the fracture toughness of 316L steel in liquid lead with a saturated oxygen concentration at 350 °C. Optical and SEM examinations complement the analyses. Full article

‘Jinyan’ is an interspecific hybrid kiwifruit (Actinidia eriantha × A. chinensis). It is a large, yellow-fleshed fruit with good taste and long storage potential. It is commonly referenced that storage potential is linked to the harvest maturity of the fruit and the subsequent temperature management. Hence, the findings from research covering the maturation, storage temperatures, ripening, and quality of ‘Jinyan’ fruit from the same orchard across three seasons have been evaluated with an overall objective of defining harvest and storage criteria for ‘Jinyan’ fruit. Good postharvest performance includes fruit not becoming too soft too soon in storage and retaining firmness at shelf temperatures. It was confirmed that harvest maturity is critical to the good storage performance of ‘Jinyan’ kiwifruit. Harvest time significantly affected fruit softening during cold storage, and treatment with the ethylene action inhibitor 1-methylcyclopropene slightly delayed fruit softening. Harvesting much before 180 days after full bloom, or at <9% soluble solids content (SSC), resulted in high incidences of chilling injury (41.8–52.0% after 24 weeks of cold storage at 1 °C + 7 d at 20 °C). These chill-damaged, early-harvested fruits also had a high incidence of rot. Leaving the fruit on the vine much after this threshold reduced chilling injury, but increased the risk of rot on otherwise sound fruit (total rot incidence ranging from 25.9% to 89.0% depending on maturity at harvest). As well as chilling risk, early-harvested fruit may reduce the consumer’s liking of the fruit because of a reduced ripe fruit SSC (rSSC). Consumer liking may also be reduced for long-stored fruit in years of low fruit dry matter content. The impact of low rSSC on consumer liking and the presence of any threshold values requires confirmation. These findings define a clear indication of when fruit should be harvested for long storage, whilst minimizing the risk of disorders. Full article

While vanadium redox flow batteries (VRFBs) are considered a promising technology for grid-scale energy storage, the combined influence of electrical load and electrolyte flow rate on overall system performance is often simplified in existing models. A MATLAB/Simulink-based system-level model of a 1 kW vanadium redox flow battery (VRFB) was developed to investigate the influence of load variation and electrolyte flow rate on battery performance. The model accounts for the flow-dependent behavior of key electrochemical parameters, including open-circuit voltage, internal resistance, and polarization losses. State of charge (SOC) is estimated using the Coulomb counting method, and a lumped first-order thermal model is included to represent stack temperature dynamics. The impact of auxiliary pump power is also considered to provide a realistic assessment of system efficiency. Results show that increasing the electrolyte flow rate from 5 LPM to 30 LPM reduces concentration polarization and improves voltage stability, leading to an increase in stack-level electrical efficiency from approximately 85% to more than 92.5%. However, the improvement in overall system efficiency becomes less pronounced at higher flow rates because of the nonlinear increase in pump power consumption.Thermal analysis indicates that stack temperature rise is mainly influenced by electrical loading, whereas higher electrolyte flow contributes to enhanced heat removal and produces only a slight reduction in overall stack temperature. The study highlights the importance of considering both electrochemical performance and auxiliary energy consumption when evaluating VRFB systems and provides useful insights into the coordinated operation of load and electrolyte flow conditions. Full article

The influence of ausforming temperature on the isothermal bainitic transformation behavior of 42CrMo steel was systematically investigated using thermo-mechanical simulation, dilatometric analysis, and electron backscatter diffraction (EBSD). The results show that ausforming significantly accelerates the bainitic transformation kinetics, whereas lower ausforming temperatures lead to a progressive reduction in the final bainite fraction. This apparently contradictory behavior originates from the competitive interaction between deformation-induced mechanical stabilization of austenite and dislocation-assisted heterogeneous nucleation of bainitic ferrite. Lower ausforming temperatures result in higher retained dislocation densities, which promote early-stage nucleation while simultaneously increasing resistance to transformation interface migration and hindering carbon redistribution. As a consequence, the bainitic ferrite microstructure is markedly refined, exhibiting reduced lath thickness and length. Crystallographic analysis reveals that the bainitic ferrite predominantly follows the Kurdjumov–Sachs orientation relationship with prior austenite, and that strong variant selection is induced by ausforming, particularly at lower deformation temperatures. The reduced variant multiplicity within individual prior austenite grains further contributes to the refinement and preferential orientation of the bainitic microstructure. These findings highlight the critical role of ausforming temperature in governing the coupled evolution of transformation kinetics, phase fraction, and crystallographic characteristics during bainitic transformation and provide guidance for microstructural control of bainitic steels through temperature-dependent thermo-mechanical processing. Full article

Solid-state heat pumps based on caloric effects are emerging as a promising alternative to conventional vapor. compression systems owing to their use of solid refrigerants with zero global warming potential. However, single-effect caloric technologies are intrinsically limited by the temperature-dependent nature of the caloric response, which typically exhibits a peak adiabatic temperature change within a narrow temperature range. In this context, multicaloric approaches offer a promising pathway to enhance thermal performance by combining multiple external fields. This work focuses on the comparison between simultaneous and sequential (cascade) multicaloric operation, with particular attention to the interaction between field application and the temperature-dependent caloric behavior of the material. A finite element model is developed to investigate a multicaloric solid-state heat pump operating in the air conditioning temperature range. A representative material is considered: Mn_0.6Ni_0.6Fe_0.4Co_0.4Si_0.95Ga_0.05, characterized by distinct magnetocaloric and barocaloric responses occurring at different temperature ranges. The analysis explores different field application strategies, including both simultaneous and sequential configurations. The preliminary results suggest that simultaneous multicaloric operation enables a more effective exploitation of the caloric response by aligning the field activation with temperature regions closer to the corresponding peaks. In this framework, cascade strategies appear to offer additional flexibility in tuning system performance under realistic operating conditions. The proposed approach provides a new perspective for the design of multicaloric heat pumps, highlighting the potential role of thermodynamic matching between field activation and material response. Ongoing work is focused on further quantifying these effects and identifying optimal operating conditions. Full article

AMn₇O₁₂ perovskites (with A = divalent elements) show complex structural and magnetic transitions including incommensurate orbital density waves and coupled/decoupled modulated spin helicity originating from charge-ordered Mn³⁺/Mn⁴⁺ cations with the 3:1 ratio at the B perovskite sites and unusual apically compressed Jahn–Teller distortions of MnO₆ octahedra. The same Mn³⁺:Mn⁴⁺ ratio can be achieved in RCuMn₆O₁₂ compositions, where R is a trivalent rare-earth cation. Therefore, the comparison in behavior of AMn₇O₁₂ and RCuMn₆O₁₂ is of interest. In this work, the A-site-ordered quadruple perovskite NdCuMn₆O₁₂ was prepared by a high-pressure high-temperature method. Its structural properties were investigated by synchrotron powder X-ray diffraction between 100 K and 350 K and laboratory powder X-ray diffraction between 5 K and 300 K. It shows a first-order structural phase transition from Im-3 symmetry (at high temperatures) to R-3 symmetry near 292 K. The structural transition is accompanied by charge (Mn³⁺/Mn⁴⁺) and unusual orbital (on the Jahn–Teller active Mn³⁺ cations located in MnO₆ octahedra) orders. However, no additional structural/orbital modulations were found at lower temperatures in comparison with AMn₇O₁₂. Magnetic properties were investigated by temperature- and field-dependent magnetization and specific heat measurements, where a ferrimagnetic transition was found near 120 K. In addition, low-temperature magnetic anomalies were observed near 20 K, probably originating from the Nd sublattice. Full article

The accurate characterization of low-power near-infrared LEDs typically requires costly radiometric equipment, limiting broader accessibility. This study proposes a low-cost indirect method for comparative NIR LED characterization based on the thermal response of black-coated aluminum absorbing targets monitored by a commercial MLX90614 contactless temperature sensor integrated with an ESP32 acquisition system. The absorbed optical power was estimated from a steady-state energy-balance model combining convective and radiative heat transfer, with geometry-dependent effective coefficients derived for 10 mm and 15 mm diameter targets. Experiments were conducted using 850 nm and 940 nm LEDs at drive currents between 30 mA and 100 mA. The absorbed power increased linearly with the drive current and electrical input power across all configurations, with R² values of 0.995–0.997 and 0.996–0.999, respectively. The 15 mm targets exhibited higher capture ratios (10.4–11.9%) compared to the 10 mm targets (8.4–9.4%). The combined measurement uncertainty ranged from 13% at high drive currents to nearly 70% at low drive currents, with the temperature-rise sensitivity being the dominant factor; within the recommended operating range (≥70 mA for 10 mm and ≥80 mA for 15 mm targets), the uncertainty remained below 25%. The proposed platform enables reliable comparative characterization of low-power NIR emitters using exclusively off-the-shelf components. Full article

This study investigated the effect of ethanol on the relative headspace percent composition of evaporative emissions from gasoline at different temperatures using HS-SPME-GC-MS. The results showed that the relative abundance of monoaromatics in the headspace decreased with increasing ethanol content in all tested fuels at all temperatures examined. The paraffins and i-paraffins exhibited a similar decreasing trend in most samples, with reductions more pronounced in E20 (20% ethanol content) than in E10 (10% ethanol content) fuels. The experimental results for the temperature effect on headspace composition were variable: monoaromatics showed slight increases at higher temperatures, whereas paraffins, iso-paraffins, and mononaphthenes generally decreased. However, ethanol addition did not significantly alter these temperature-dependent trends, as similar patterns were observed in both ethanol-blended and ethanol-free fuels. The magnitude of the ethanol effect depended on fuel composition, with the largest reductions in monoaromatic hydrocarbons observed for the high-density gasoline samples. These findings demonstrate that ethanol modifies the relative distribution of hydrocarbon classes in gasoline headspace, with the most pronounced effect being a reduction in monoaromatic hydrocarbons, and highlight the value of class-resolved analysis for understanding fuel evaporation behavior. Full article

Induction heating is widely used in industrial processes such as forging, hardening, and additive manufacturing, but its accurate numerical simulation requires coupled electromagnetic and thermal finite element analyses with nonlinear, temperature-dependent material properties. This work proposes a deep learning surrogate model based on a convolu-tional neural network for TEAM Workshop Problem 36, a reference benchmark for nonlinear magneto-thermal induction heating. A database of more than 40,000 finite element solutions was generated by varying the supply current from 2 to 6 kA and the frequency from 2 to 6 kHz, while accounting for transient nonlinear effects, including the Curie transition. The network, composed of 24 layers with transposed convolutions, batch normalization, and dropout, maps current, frequency, and time to radial temperature distributions in the steel billet. For most operating conditions, the model achieves mean absolute percentage errors of about 6–7% for radial line in the middle of the billet and about 10% for radial line close to the billet end. Larger discrepancies occur during the early heating stage and near the Curie temperature. Prediction times are reduced by three to four orders of magnitude with respect to a single finite element analysis. The results indicate that the proposed surrogate enables fast temperature estimation for optimization, digital twins, and closed-loop control of induction heating systems. Full article