Search Results (700)

Spacer wires are widely employed in lead-cooled fast reactor fuel assemblies to maintain rod positioning. The helical spacer structure induces rotational flow and enhances transverse mixing between subchannels, thereby significantly influencing thermo-hydraulic performance. To further regulate coolant mixing intensity and reconstruct internal flow structures, a double-wire configuration with variable radial phase differences is proposed. Three-dimensional steady RANS simulations of liquid lead–bismuth flow in a 19-pin double-wire fuel assembly are conducted using a four-equation turbulent heat transfer model. Results indicate that pressure and velocity fields exhibit periodic distributions along the helical direction, with a clear inverse correlation between high-pressure and high-velocity regions. Transverse secondary flow intensity shows pronounced axial periodicity and attains a maximum value of 0.32, with stronger mixing observed in the vicinity of the spacer wires. Peripheral and corner subchannels maintain lower average coolant temperatures, whereas peak temperatures are concentrated within internal subchannels. The overall convective heat transfer coefficient decreases gradually along the axial direction and presents a localized enhancement in the mid-axial region. The axially averaged convective heat transfer coefficient of DP60 is approximately 4.58% higher than that of DP90. This difference is a thermal comparison and does not establish overall thermo-hydraulic superiority. Peak modeled coolant temperature fluctuations are observed at the interface between peripheral and outer internal subchannels, while maximum turbulent Prandtl numbers are concentrated within internal subchannels. Full article

Waste cooking oil is a valuable feedstock for renewable biofuels via hydrodeoxygenation reactions. This study presents a novel strategy with nickel catalysts supported by carbon derived from waste tire rubber (Ni/C). The findings reveal the synthesis of renewable biofuel with diesel-like properties. Under the investigated conditions, optimal yields of 70.12% and 96.5% are achieved for n-C₁₇ and the total C₁₀–C₁₈ alkane fraction, respectively. To achieve them, we conducted 246 hydrodeoxygenation reactions in a stainless-steel batch autoclave with a vertical four-blade agitator; the impeller was operated in alternating rotation at 120 rpm to ensure comprehensive radial and axial mixing. For each one, 0.9 g of the Ni/CTR catalyst was used, varying reaction inputs: system pressure (20–25 bar), active metal loading of the catalyst (5–10 wt.% Ni), isothermal reaction temperature (320–340 °C), and reaction time (4–5 h), obtaining output variables as the molar yields of catalytic n-C₁₇ (dynamic range: 36.78% to 63.03%) and the global yield of the C₁₀–C₁₈ alkane series (50.99% to 88.98%). After that, we trained and evaluated 2500 distinct neural network configurations to identify the optimal architecture. The best model achieved R² values of 0.9525 for the C₁₀–C₁₈ alkane series and 0.9544 for n-C₁₇, with error metrics of MSE, MAE, and MAPE at 0.0019, 0.0388, and 9.54%, respectively. Finally, we conducted 1000 simulations, increasing input ranges and step sizes, varying reaction parameters, and predicting yields using the neural network to identify the maximum alkane production. This led to improvements in n-C₁₇ and total alkane (C₁₀–C₁₈) yields of 11.25% and 8.45%, respectively. Full article

Non-contact diffuse reflectance to below-surface absorption disguised by a thick superficial layer is challenging to instrument and model. We develop a semi-empirical “capsule” model of non-contact diffuse reflectance, configured as center-illuminated-area-detection (CIAD), to model below-surface absorption. The “capsule” approach extends a principle of modeling the effect of a thin (<1 mm) top layer on radially resolved diffuse reflectance for contact probing to the effect of a thick (1~3 mm) surface layer on radially integrated CIAD diffuse reflectance for non-contact probing. The model treats diffuse reflectance of CIAD from a two-layer medium by weighing between two limiting cases of monolayer taking either the top or bottom of the two-layer properties. The semi-empirical model of CIAD diffuse reflectance over an area of a radius of ≤15 mm responding to variation of single inter-layer contrast is examined against Monte Carlo simulations of two-layer media with a 1–3 mm top layer, three orders of magnitude change in absorption, and two orders of magnitude change in reduced scattering. Compared to MC simulations, the modeled CIAD diffuse reflectance of the two layers gives total ensemble errors of up to 18.6% and 12.2% over the range of a single inter-layer contrast of absorption and reduced scattering, respectively. The results provide insights into the challenges of using CIAD diffuse reflectance to assess spectral absorption of the below-surface layer, which will be examined experimentally in a subsequent paper. Full article

The mathematical analysis of the hyperbola is extended to distinguish and compare several angles which are important to physical applications, e.g., comets and Rutherford scattering. We quantify the impact angle, which plays a key role in angular momentum conservation, and distinguish it from the angle of deflection emphasized in historical analyses of gravitational bending of light. We elucidate requirements for collinear arrangement of points on opposite limbs with the focus, which configuration pertains to analysis of galaxy images for possible gravitational lensing effects. These geometrical relationships are obtained by transforming the curved trajectory of a mass propelled by Newtonian gravitational forces in polar (R, θ) or conventional Cartesian (x, y) Euclidean space into linear trajectories in Y, R or X, R space, where R, X, and Y are radial and Cartesian distances to the focus, now located at X = 0 and Y = 0. These coordinate transformations simplify geometric analysis of orbits and trajectories, as they allow any conic section to be recast into the compact linear form, R = eY + L, where e is the standard eccentricity and L is the length of the semi-latus rectum. Our formulae specify the limitations of approximations used in physical analyses of light bending, such as considering only asymptotic behavior and small angular deviations. Here we quantitatively describe the entire hyperbolic path, which should be useful in many applications. Full article

Conventional five-degree-of-freedom (5-DOF) magnetic bearing supports often require a large axial span, while highly integrated magnetic circuits can introduce axial–radial flux coupling through shared return paths. This study proposes a compact permanent-magnet-biased 5-DOF magnetic bearing for flywheel energy storage systems, integrating two radial support sections and one axial support unit within a common stator. A series-opposed compensation winding is introduced to suppress axial-control-induced leakage into the radial branch. An electromagnetic design procedure considering leakage, ampere-turns, and magnetic-saturation constraints is evaluated using a three-dimensional magnetostatic finite-element model. At 6 A, the modeled axial and radial forces reach approximately 1.50 and 0.75 kN, respectively, while the maximum ferromagnetic flux density remains below 1.25 T. Under permanent-magnet-biased operation, the compensation winding reduces the peak radial-field deviation from approximately 161.5 to 1.7 mT, corresponding to approximately 99.0% suppression; the full-path RMS-deviation metric indicates approximately 93.1% suppression. Among the investigated configurations, the one with 50 turns provides the closest restoration to the bias-only radial field. Prototype tests demonstrate stable five-channel closed-loop static suspension, supporting physical realizability, but do not directly validate the predicted decoupling ratios. Full article

Hybrid electric vehicle (HEV) front-face styling is jointly constrained by functional requirements for engine intake, radiator cooling, and thermal management and by demands for brand identity and emotional expression. Existing Kansei engineering studies have largely focused on whole-vehicle exteriors or generic electrified vehicles, paying insufficient attention to the functional boundaries of HEV front grilles. Moreover, culturally informed automotive styling often relies on designers’ subjective associations and lacks a coherent design pathway. To address these gaps, this study proposes a rough-set-driven Kansei design method for HEV front faces under cultural-semantic constraints. First, an entropy-weighted neighborhood rough-set method is used to identify key Kansei requirements. A rough-set-induced hybrid-kernel prediction model is then constructed by combining rough-set indiscernibility relations with nonlinear similarity, thereby mapping discrete front-face morphological features to users’ Kansei evaluations and predicting the performance of different morphological combinations. Finally, the resulting design knowledge is integrated with the structural characteristics of traditional motifs to generate culturally oriented front-face concepts. Results identified power, premium quality, and approachability as the three key Kansei requirements for HEV front faces. The proposed rough-set-induced hybrid-kernel support vector regression (RSIHK-SVR) model achieved a mean coefficient of determination (R²) of 0.927 and a root mean square error (RMSE) of 0.157 on the test set. Compared with the optimized standard radial basis function (RBF) kernel models and the single rough-set-induced-kernel model, RSIHK-SVR achieved the highest predictive accuracy on the test set (R² = 0.927, RMSE = 0.157), improving R² by 0.8–13.3% and reducing RMSE by 3.1–35.9% across the comparator models, thereby confirming the effectiveness of the hybrid-kernel strategy. The model-predicted morphological configurations were then integrated with the structural characteristics of bronze animal-mask, ice-crackle lattice, and fangsheng motifs to develop three front-face concepts targeting power, premium quality, and approachability, respectively. User evaluations further showed that all three concepts effectively communicated their intended Kansei semantics and exhibited favorable cultural-semantic compatibility. The proposed method thus provides quantitative decision support for conceptual HEV front-face designs with cultural identity and differentiated styling. Full article

To clarify the effects of splitter blades on hydraulic performance and internal energy dissipation in a double-suction pump as turbine (PAT), full-passage CFD models of a PAT and a PAT with splitter blades were established and experimentally validated. Same-flow-rate cross-comparisons at the BEP flow rates of the configurations distinguished geometric effects from flow-rate effects. Impeller loss redistribution was analyzed using entropy generation, LEGR, TKE, and radial-flow characteristics. The splitter blades shifted the BEP flow rate from 1350 to 1708 m³/h, an increase of 26.52%, and increased the maximum efficiency from 85.61% to 87.72%. Turbulent and wall entropy generation dominated the loss, whereas direct viscous entropy generation contributed less than 1%. At the prototype BEP flow rate, the normalized volumetric entropy-generation coefficient over Regions I–O decreased by 10.31%; at the splitter-blade BEP flow rate, the reduction reached 60.71%, with Region M decreasing by 66.33% and providing the dominant absolute loss reduction. At the higher flow rate, splitter blades restricted the lateral expansion of low-velocity regions, weakened large-scale separation and continuous high-LEGR shear structures, and confined the remaining high-loss regions to blade leading edges, splitter-blade wakes, and local flow-recombination zones. These results show that splitter blades improve high-flow-rate performance by suppressing separation- and shear-related volumetric dissipation and redistributing impeller energy losses. Full article

TinyStressNet is a compact neural classifier for three-class academic stress estimation (low, medium, high) from three physiological features (galvanic skin response, heart rate, and skin temperature) designed for low-cost educational sensing. We evaluate it on 1000 interval-level observations from five engineering students collected over three months, with labels derived from repeated 6-item short-form of the State-Trait Anxiety Inventory (STAI-6) self-reports aligned with contemporaneous physiological readings. For subject-independent evidence, we use leave-one-subject-out (LOSO) evaluation as the primary protocol, complemented by a per-user chronological split for temporal robustness. We study augmentation through the lens of approximate invariance to bounded, label-preserving nuisance transformations, comparing no augmentation, Gaussian jitter, a radial-rescaling family, and a bounded affine (BA) family against strong classical baselines (Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), and Support Vector Machines (SVMs), logistic and ordered-logit models). Under LOSO, the best TinyStressNet configuration reaches 0.899 accuracy and 0.898 weighted F1; within users, it reaches 0.912 accuracy. The model uses 3139 parameters and 2800 Multiply-Accumulate operations (MACs), and post-training int8 export preserves predictions with almost the same accuracy (0.992 float–int8 agreement). Strong classical baselines remain competitive on this low-dimensional representation, which we read as evidence about the geometry of the three-feature space rather than as a limitation of the model. Repeating the full evaluation under ten seeds shows that the augmentation families are not separable on this representation: subject-independent weighted F1 spans 0.894 to 0.900 across the four conditions with a seed-to-seed standard deviation of about 0.005, and no augmentation is not measurably worse than the best family. The BA family is the most consistent condition, the strongest in five of ten seeds and never the weakest, which we report as a stability observation rather than a performance gain. TinyStressNet is presented as a compact, quantization-ready reference model and a controlled testbed for invariance-aware augmentation in low-dimensional physiological sensing. Full article

Reliable attribution of artificial intelligence (AI)-generated text to a specific large language model (LLM) matters increasingly as LLMs proliferate, yet where quantum machine learning actually stands on this task has, to our knowledge, never been measured systematically. We benchmark the quantum support vector machine (QSVM) for binary attribution between Gemma 3 and Qwen 2.5 on a 5800-sample corpus from paired prompts: 83 configurations sweeping qubit count, regularization, training-set size, feature-map family, and circuit depth under exact, noiseless classical statevector simulation. QSVM validation accuracy plateaus at approximately 88%, whereas a classical support vector machine with a radial basis function kernel reaches approximately 97.8% on the identical fourteen-dimensional inputs: the ceiling belongs to the quantum (fidelity) kernel, not to the input representation. We measure the mechanism: off-diagonal quantum kernel values shrink exponentially with qubit count, the signature of exponential kernel concentration. The same classical model recovers the stylometric attribution fingerprint, showing it belongs to the shared feature pipeline rather than to the quantum kernel. All large-scale headline results generalize to an independent 1000-text test set produced after every design decision was frozen. The study provides a cautionary, reproducible benchmark for quantum kernel natural language processing and outlines an open-set extension as future work. Full article

Water-decking can buffer and redistribute borehole loading, but the coupled effects of axial charge segmentation, radial decoupling, and peripheral-hole spacing across scales remain insufficiently quantified. A cross-scale three-dimensional multi-material Arbitrary Lagrangian–Eulerian (ALE) framework coupled with the Riedel–Hiermaier–Thoma (RHT) damage model was developed for intact granite and applied at single-hole, double-hole, and full-face scales following specimen-scale calibration and numerical consistency checks. Increasing the segment count from four to six reduced the charge-section peak pressure from 283.0 to 257.0 MPa while increasing the water-section peak from 24.5 to 50.7 MPa. Increasing the radial decoupling coefficient from 1.00 to 1.31 reduced the numerical damage span from 55.6 to 33.7 cm. The spacing–decoupling assessment identified the six-segment configuration with K_d = 1.31 and 65 cm spacing as a condition-specific combination that maintained inter-hole damage connectivity while limiting outward disturbance. In the full-face model, multi-hole stress-wave interaction occurred at approximately 0.48–0.52 ms. The D ≥ 0.19 and D ≥ 0.90 damaged regions occupied 2.154% and 0.348% of the representative section, respectively. These results support a sequential axial–radial–spatial regulation framework linking pressure redistribution and inter-hole interaction to full-face stress and damage evolution, providing a basis for smooth-blasting parameter selection under the investigated intact-granite conditions. Full article

This study addresses the challenge of temperature non-uniformity during carbon fibre-reinforced polymer (CFRP) composite patch repair, which compromises curing quality and process efficiency. A coupled heat transfer–curing kinetics finite element model was developed and experimentally validated to investigate the heat sink effect of support structures. Key findings reveal that temperature differences concentrate near aluminum components and increase with curing temperature. For the present scarf-repair configuration, global sensitivity analysis identified the second-stage holding temperature (T₂) and heating rate (r₂) as the dominant factors governing temperature uniformity, whereas the holding times (dt₁ and dt₂) primarily determine the total curing time (t_total). A novel multi-objective optimization framework combining optimal Latin hypercube sampling, radial basis functions, and NSGA-II was established. The optimized curing profile achieves a surrogate-predicted reduction of 22.5% in maximum temperature difference (22.0% when confirmed by high-fidelity finite element verification) and 36% in total curing time, while maintaining a minimum degree of cure above 0.98. These results provide a validated, surrogate-based framework for designing curing protocols that resolve metal-induced thermal non-uniformity in composite repairs without sacrificing cure quality. Full article

A distribution feeder is built meshed and operated radially, so at any instant it occupies one of a combinatorial family of topologically radial configurations. We show that this family, weighted in the natural maximum-entropy way, is a determinantal point process whose kernel is the transfer-current matrix of the network, and we read that kernel in the operator’s language: the probability that a line section is energised equals its own self transfer-current factor, Foster’s sum rule is the trace identity, and the covariance of two switching states is minus the square of their normalised transfer current. Independent faults leave the feeder exactly within this family for any number of faults, whereas no restoration mechanism ignorant of the section resistances can return it there; among those that can, one is canonical, being the unique mechanism that reverses the fault, and its weight is the section’s transfer-current factor in the post-fault network with everything still energised shorted. We show, and report, that these weights are a structural diagnostic and not a repair priority. The maintained feeder is solved in closed form, and an exact transport equation prices what a reinforcement programme costs the feeder’s ability to reconfigure. The central spanning-tree and sector identities are verified against exhaustive enumeration; the dynamical and sensitivity statements are checked by exact master-equation computations and finite differences. Full article

Molecular dynamics simulations examined the roles of molecular structure, thermodynamic compatibility, intermolecular association, and mixture composition in the supercritical CO₂ extraction of ten crude oil components at 363.15 K and 15 MPa. Single-component extraction ratios ranged from 80.70% for n-hexane to 5.85% for 2-naphthol. Compounds of similar size differed widely, indicating that topology, aromaticity, and polar functional groups were more informative than molecular size alone. CO₂ solubility parameters obtained from MD agreed with estimates derived from NIST data, and δ_CO2 = 7.28ρ_r captured their reduced density dependence over 303.15–363.15 K. Extraction generally decreased with increasing oil–CO₂ solubility parameter difference. In binary systems evaluated using oil boundaries determined by the half density criterion, higher fractions of nonpolar partners were associated with increased total extraction ratios, whereas higher fractions of polar partners were associated with decreases. Multicomponent systems showed redistribution that depended on the overall composition, and relative diffusion coefficients qualitatively reflected mobility differences. The gas–oil interaction competition factor, R_comp, decreased from 1.985 to 0.087 in the same order as the extraction ratios. Both the thermodynamic and energetic correspondences persisted after excluding 2-naphthol. Configurations and radial distribution functions showed that association in nonpolar hydrocarbons was dominated by dispersion interactions, whereas polar and aromatic components exhibited additional hydrogen bonding, aromatic stacking, and dipolar or electrostatic organization. Local CO₂ enrichment near polar sites alone did not explain overall extraction. Overall, the selective transfer of individual components was consistent with a balance between local CO₂–oil association and collective oil–oil cohesion that depended on mixture composition, while molecular organization may regulate the accessibility of favorable CO₂ contact sites. Full article

To address the challenges of rapid voltage fluctuations and operational economy in new power systems with high wind power integration under sandstorm weather, this paper proposes a multi-timescale cooperative voltage control strategy for new power systems. On the second-level timescale, a discrete state-space model of wind turbines and reactive power devices is established considering sudden wind speed changes. Model predictive control (MPC) is then used to rapidly calculate the optimal reactive power references for wind turbines, static var generator (SVG), and on-load tap changer (OLTC), thereby effectively ensuring rapid stabilization of the grid-connection point voltage. On the minute-level timescale, a two-stage topology reconfiguration method is adopted. A feasible radial network is first generated through a sequential switch opening strategy, followed by iterative optimization via a switch exchange strategy. This approach rapidly identifies the optimal switch configuration to minimize network losses and improve operational economy. Simulation results demonstrate the effectiveness of the proposed strategy in voltage regulation and loss reduction, highlighting its capability to enhance the robustness of new power systems under sandstorm weather. Full article

This study numerically investigates the influence of strut diameter on the deployment behavior of a balloon-expandable biodegradable stent with rhombic cell architecture using finite element analysis. The stent material was represented by a 60/40 poly(lactic acid)/polydioxanone (PLA/PDO) blend. Four stent configurations with strut diameters of 0.15, 0.25, 0.35, and 0.50 mm were analyzed under identical deployment conditions. The numerical evaluation considered von Mises stress together with five deployment indicators: diametral strain, elastic recoil, dog-boning, foreshortening, and longitudinal retraction. The results show that increasing the strut diameter reduces elastic recoil, foreshortening, and longitudinal retraction, thereby enhancing post deployment dimensional stability. However, thicker struts also increase the dog-boning effect, indicating less uniform radial expansion. Among the investigated designs, the stent with a 0.35 mm strut diameter showed a balanced response between deployment uniformity and post deployment mechanical stability under the adopted numerical assumptions. For this configuration, elastic recoil, foreshortening, longitudinal retraction, and dog-boning were approximately 6.2%, 10%, 37%, and 8.9%, respectively. These findings provide practical design guidance for biodegradable polymeric vascular stents. Full article