Search Results (1,306)

Accurate measurements of global horizontal irradiance (GHI) are fundamental for solar energy assessment. However, the cost and deployment constraints of standard pyranometers limit their widespread use. This work presents a low-cost pseudo-pyranometer based on photovoltaic current measurements combined with a hybrid physical-machine learning approach. A custom data acquisition system was developed and deployed in Piatra-Neamț, Romania, consisting of a Raspberry Pi 5, INA219 current sensor, and a 0.3 W photovoltaic panel mounted horizontally. One-minute resolution measurements were collected between August 2024 and June 2025 and augmented with modeled solar geometry and clear-sky irradiance using pvlib. Temporal effects were encoded using sinusoidal representations of the time of the day and the day of the year. Clear-sky current samples were identified using a tolerance-based normalization with respect to modeled clear-sky irradiance and used to train an artificial neural network to estimate the clear-sky panel current. Feature importance was assessed using SHAP analysis, highlighting the dominant role of solar geometry and temporal encoding. The resulting clear-sky current model was combined with measured current through a clearness index formulation to estimate GHI. To evaluate performance, the system was redeployed in parallel with a reference pyranometer in Cluj-Napoca, Romania, enabling direct comparison under real operating conditions. The results demonstrate that the proposed hybrid approach can approximate pyranometer measurements with low-cost hardware, supporting scalable and redeployable solar monitoring networks in geographically localized regions. Full article

The increasing deployment of wind energy has brought renewed attention to aeroacoustic noise generated by wind turbine blades, where broadband noise is primarily associated with vortex shedding at the trailing edge (TE) and leading edge (LE) of airfoils. Owls, particularly Tyto alba, exhibit wing morphologies such as serrations, velvet-like surfaces, and fringes that enable silent flight through aerodynamic noise suppression. This study presents a scoping review of the scientific literature on owl-inspired serration strategies applied to aerodynamic airfoils and wind turbine blades. The literature search was conducted across major academic databases, including Scopus, ScienceDirect, SpringerLink, and MDPI, covering publications from 1970 to 2025. A total of 69 experimental and numerical studies focusing on LE and TE serrations was analyzed. The review integrates aeroacoustic analysis with bio-inspired design perspectives. The analyzed studies consistently show that serrated geometries modify vortex dynamics and turbulence structures, leading to measurable acoustic benefits. Experimentally, the largest reductions reported for aerodynamic airfoils reached about 7 dB for both LE and TE serrations, mainly as broadband noise attenuation, in specific frequency ranges. Numerically, the highest reported reduction reached up to 21 dB for a serrated TE configuration, corresponding to spectral SPL reduction mainly below 1.6 kHz. The reviewed studies also indicate that the associated aerodynamic response is strongly configuration-dependent, ranging from limited penalties to measurable changes in lift, drag, power output, or structural loading. Numerical simulations further support experimental findings and highlight the importance of geometric parameters such as serration amplitude, wavelength, and spacing. Overall, bio-inspired serrations represent a promising passive strategy for aeroacoustic noise mitigation in wind turbines, drones, and rotating aerodynamic systems. Future research should focus on the multi-objective optimization of serration geometry, large-scale experimental validation, and the integration of bio-inspired concepts into industrial blade designs. Full article

Die swell is the dominant source of dimensional deviation in rubber profile extrusion. Because it is driven by recoverable elastic strain, a purely viscous baseline flow field cannot reproduce its speed dependence; a viscoelastic correction is required. This study presents, to the best of our knowledge, the first controlled comparison of a Carreau–Arrhenius baseline flow field against a fractional-order viscoelastic correction for carbon-black-filled EPDM across an industrial speed window. The viscoelastic correction (PyCFD-FMM) is a post-processing fractional-order viscoelastic swell correction built on the shared non-isothermal Polyflow Carreau–Arrhenius flow field, derived from a six-mode fractional Maxwell model parameterized from dynamic mechanical analysis via the Laun rule and closed through the Tanner recoverable-strain theory. Three carbon-black-filled EPDM compounds (Shore A 60–80) were extruded at four screw speeds (15–30 rpm) under instrumented conditions. Experimentally, swell ratios of 1.12–1.15 increase monotonically with screw speed (Fisher-combined $p=0.007$; measurement repeatability CV $\le 0.27$% across $n=4$ replicates per condition). The purely viscous baseline output gives a decreasing apparent swell–speed trend—opposite to experiment—whereas PyCFD-FMM recovers the correct increasing trend for all compounds. Under single-anchor hold-out evaluation at 20/25/30 rpm, the non-anchor MAPE decreases from 0.99% for the baseline flow-field output to 0.30% (PyCFD-FMM); an anchor-sensitivity check over all four rpm choices keeps the compound-averaged non-anchor MAPE within 0.27–0.39% and preserves the correct slope sign in every case. Swell decomposition into geometric baseline and net correction factor ($B_{\mathrm{PyCFD}}=B_{\mathrm{geom}}\times f_{\mathrm{corr}}$) confirms that the viscous baseline flow field captures flow-geometry effects but carries no elastic memory. Within the tested window, the viscoelastic correction meets a dual-gate criterion—correct slope sign and reduced non-anchor MAPE—which the purely viscous baseline cannot satisfy by construction. Full article

The Real Maestranza de Caballería in Seville features one of the most prominent Spanish bullrings, characterized by a notable architectural design. Its distinctive ovoid geometry resulted from a protracted construction history (1761–1881), during which the floor plan adapted to pre-existing urban structures. Beyond its architectural significance, the sounds perceived within such venues constitute traces of collective memory and form part of an intangible cultural heritage relevant for understanding the sociocultural context of such spaces. This work provides an acoustic characterisation of the bullring through field measurements. Reverberation time and other monaural and binaural descriptors were determined using 3D impulse responses obtained from strategically placed sources and receivers. This analysis is complemented by examining the sound energy distribution of early reflections in the time–frequency domain to define the acoustic signature of the venue, namely the characteristic pattern of early reflections that unequivocally determines its sound response, and identify the provenance of reflections. In the Maestranza, music and silence are hallmarks of its identity, contributing to a complex auditory environment. The results highlight how its geometry and tiered seating create a differentiated sound field, potentially contributing to the preservation of the site as a cultural landmark. Full article

Accurate and reproducible delineation of stream bankfull geometry remains a persistent challenge in environmental planning. To address this gap, we developed the Cross-Sections and Dimensions Tool, a semi-automated, slope-based method for extracting stream cross-sections and estimating bankfull width, elevation and depth using high-resolution elevation data. The tool applies a configurable slope threshold to identify bank edges, generates perpendicular cross-sections from a stream centreline, and stores all outputs in a structured geodatabase to ensure transparency and reproducibility. Validation against manually delineated bankfull polygons across 191 km of stream length in Greater Melbourne, Australia, demonstrated strong spatial agreement, with an average F1 score (a measure of prediction-observation overlap) of 74% and a mean absolute error of 0.64 m in bankfull elevation. The tool was most reliable in larger streams (Strahler order 5 and above) with low to moderate vegetation canopy cover (<80%). We also investigated the practical visibility limits of small or indistinct channels typically encountered by human mappers and verified that the tool did not produce unrealistic channel delineations. This approach advances geomorphic feature extraction by grounding bankfull delineation in deterministic geometry rather than hydrological recurrence or data-driven modelling. In practice, it enables scalable, transparent, and repeatable analysis of stream morphology for ecological assessment, infrastructure planning, and waterway management. Full article

Objectives: Several measurement techniques have been proposed to address the non-circular geometry of the aortic root. The Laplace diameter metric incorporates the cloverleaf anatomy of the aortic root and is derived via measurement of sinus-to-commissure lengths with subsequent doubling of the largest radius from the center. This study compares the conventional sinus-to-sinus with the novel Laplace method for sizing the aortic root and quantifying its implication on surgical decision-making. Methods: Patients undergoing surveillance at a high-volume aortic center were categorized by aortic root morphology as nondilated, non-syndromic dilated, bicuspid aortic valve and Marfan syndrome. Aortic root diameters by sinus-to-sinus and Laplace diameter methods were measured on computed tomography, compared using paired t-tests, and correlated using Spearman rank coefficients. Results: Of the 1297 patients assessed, 530 were included in the final analysis (nondilated n = 113, non-syndromic dilated n = 347, bicuspid aortic valve n = 50, Marfan syndrome n = 17). Aortic root diameters were significantly larger by Laplace than sinus-to-sinus diameter across all groups (sinus-to-sinus: 1.9 ± 5.5 mm; Laplace: 44.9 ± 7.0 mm; 95% confidence interval 2.72–3.34; p < 0.0001). Although Laplace and sinus-to-sinus diameter were correlated (Spearman r = 0.6789, 95% CI 0.6–0.7; p < 0.0001), the relationship was non-linear (R² = 0.492). Laplace diameter increased the proportion of patients meeting surgical thresholds (2022 AHA/ACC guidelines) versus sinus-to-sinus: nondilated 0% vs. 1.77%, non-syndromic dilated 4.9% vs. 25.1%, bicuspid aortic valve 10.0% vs. 26.0%, and Marfan syndrome 23.5% vs. 52.9%. Conclusions: On average, Laplace diameter exceeded sinus-to-sinus diameter by 3 mm and would extend surgical eligibility to an additional 21% of patients under current guidelines. Full article

This study developed and validated a curriculum-aligned instrument to assess preservice primary teachers’ geometric reasoning skills. Addressing the limited availability of domain-specific tools in teacher education research, the study examined preservice teachers’ conceptual strengths and weaknesses across key geometry domains relevant to primary mathematics teaching. A two-phase quantitative research design was employed. In Study 1, Confirmatory Factor Analysis (CFA) and Item Response Theory (IRT) were used to evaluate the psychometric properties of the instrument with a sample of 221 preservice teachers, providing evidence of construct validity and internal consistency. Geometric reasoning was conceptualised as a four-factor structure comprising Conceptualisation of Geometric Properties (GP), Geometric Transformation Reasoning (GT), Reasoning with Representations of Three-Dimensional Objects (RE), and Measurement Reasoning (MS). In Study 2, the validated Geometric Reasoning Test (GRT) was administered to a larger sample of 406 preservice primary teachers from three education colleges in Myanmar. Descriptive statistics and group comparisons were conducted using Welch’s t-tests and Welch’s ANOVA to examine differences by gender, year level, and institution. The findings indicate that preservice primary teachers’ geometric reasoning remains underdeveloped across training stages, highlighting the need for greater emphasis on geometry and spatial reasoning in teacher education. Full article

This study presents a combined numerical and experimental investigation of transient multiphase compressible flow inside a profiled-rotor rotary volumetric compressor. While most existing studies rely on high-fidelity CFD approaches, a low-order thermodynamic chamber-based model implemented in MATLAB Release 2023a is proposed to predict the temporal evolution of pressure, temperature, and vapor volume fraction during the compression cycle. The model is based on mass and energy conservation applied to variable-volume control chambers and incorporates a simplified cavitation criterion derived from local pressure relative to saturation vapor pressure. An open-loop experimental test bench was developed to measure air mass flow rate, suction and discharge pressures, temperatures, torque, and shaft power under controlled operating conditions. These measurements are used to validate the numerical predictions. The results show good agreement between measured and simulated pressure levels and global performance indicators, with deviations quantified using mean absolute percentage error values remaining below 5% over the investigated operating range. The numerical analysis further reveals the occurrence of localized low-pressure zones during the suction phase, indicating incipient cavitation or microbubble formation at specific rotor positions. The proposed modeling approach provides a computationally efficient alternative to full CFD simulations and enables rapid parametric analysis of rotor geometry and operating conditions. The cavitation formulation does not aim to resolve detailed bubble dynamics or erosion mechanisms, but rather to identify cavitation tendency based on thermodynamic pressure thresholds. Full article

Single point incremental forming (SPIF) represents a flexible manufacturing process capable of producing complex sheet metal parts without the need for dedicated forming dies. However, achieving high dimensional accuracy remains a major challenge due to phenomena such as elastic springback and localized deformation. In this context, the present study investigates the influence of tool-axis orientation on the dimensional accuracy of parts manufactured through robot-based single point incremental sheet forming (RB-SPIF). The experimental analysis considered two toolpath strategies (contour and spiral), two vertical step sizes (0.5 mm and 1 mm), and two tool-axis configurations (fixed tool-axis and wall-normal tool-axis orientation), resulting in eight experimental cases. The dimensional accuracy of the manufactured parts was evaluated using optical 3D scanning and cross-sectional profile analysis. The results show that the vertical step size has a significant influence on the resulting geometry, with smaller step sizes generating profiles closer to the nominal geometry. The toolpath strategy also affects the geometry, with spiral trajectories generally producing slightly improved profiles compared to contour strategies; however, this effect was not found to be statistically significant under the investigated conditions. Furthermore, the use of a wall-normal tool-axis configuration improves the agreement between the measured and nominal profiles by enhancing the contact conditions between the tool and the metal sheet surface. These findings indicate that adaptive tool-axis orientation represents a promising strategy for improving the dimensional accuracy of parts produced by robot-based incremental sheet forming systems. Full article

Cermet tools possess favorable mechanical and tribological properties and are widely adopted for machining hard-to-cut materials. However, their performance can further be enhanced with different cooling and lubrication techniques. In this study, the tool wear mechanisms of cermet tools during hard turning of AISI 4340 alloy steel are investigated under dry and minimum quantity lubrication (MQL) environments to identify the prevalent causes of tool failure through comprehensive analysis of tool wear progression, chip temperature, and chip morphological analysis. The results revealed that the application of MQL exhibited prolonged and stable steady-state tool wear progression with retained cutting-edge geometry, thus demonstrated 30.27% improvement in tool life compared to dry cutting. On the contrary, a rapid increase in tool wear due to excessive friction and higher thermal load is noticed with dry cutting in the absence of any heat-dissipating medium. Chip temperature measurements supported these observations, as chip temperature increases sharply from 358 °C (with a fresh tool) to about 1090 °C (with a worn tool) under a dry environment. Conversely, with MQL, the corresponding increase was in the range between 294 °C and 843 °C with a fresh and worn tool, respectively. Chip analysis revealed a serrated type of chip morphology. Dry cutting exhibited intensified feed marks, indicative of severe tool–chip friction, whereas MQL demonstrated smoother morphology with closely spaced saw-tooth patterns. Tool wear mechanisms indicate abrasion, adhesion, and edge chipping as dominant wear mechanisms under both environments; however, in the absence of any lubricant, these mechanisms were more intensified with higher crater formation. Full article

Camera rotation estimation is a key component in video stabilization and motion analysis. In many practical scenarios, inertial measurements are unavailable or temporally unreliable, while classical geometric pipelines degrade under blur, low texture, and low illumination. This paper investigates whether substantially downsampled optical flow can retain sufficient structure for accurate frame-to-frame rotation regression. We present VisualRNet, a lightweight rotation-specific visual regression framework trained with cross-modal IMU supervision. Our design uses coordinate-aware feature encoding, depthwise separable convolutions, lightweight attention, and a compact 6D rotation head to model the spatial structure of rotational flow fields. On Deep-FVS, VisualRNet achieves a mean rotation error of 0.3151${}^{\circ }$ on the test set. The VisualRNet regression head contains 7.7 K parameters, 0.002 GFLOPs, and runs at 729 FPS, while the full pipeline with the FastFlowNetv2 frontend contains 1.374 M parameters, 7.194 GFLOPs, and runs at approximately 113 FPS. A cross-camera adaptation experiment on TUM VI further indicates that the learned motion representation can be aligned to a new camera system with limited calibration data. These results support low-resolution optical flow as a practical input for visual rotation estimation and suggest particular value in stabilization-oriented and cost-sensitive applications where approximate rotational trend matters more than full scene geometry. Full article

Binding affinity prediction in computational drug discovery is confounded by trivial correlations between molecular size and measured potency. We introduce cellular sheaf Laplacians as descriptors of ligand molecular geometry that quantify geometric frustration independent of system size. Sheaves are constructed over molecular graphs by assigning three-dimensional coordinate spaces to atoms and projection operators encoding ideal bonding geometry to edges; eigendecomposition of the resulting Laplacian yields spectral features measuring inconsistencies between local geometric constraints and global topology. Applied to 14,050 protein-ligand complexes from the PDBbind v2020 refined set, MW-residualized Sheaf features capture a statistically significant geometric signal ($r_{\mathrm{partial}} = 0.171$, $p<{10}^{-70}$) that is orthogonal to the Wiener index ($r=0.013$) and persists after controlling for both molecular weight and classical graph-theoretic descriptors ($r_{\mathrm{partial}} = 0.390$, $p<{10}^{-9}$). Sheaf spectral features alone achieve predictive performance ($R^2=0.403$) approaching that of fourteen classical cheminformatics descriptors ($R^2=0.446$), and their combination yields consistent improvements across the binding affinity spectrum (RMSE $=1.43$$p{K}_d$). Permutation importance analysis confirms the Sheaf Frobenius norm as the second most influential descriptor after molecular weight. We introduce Topological Binding Efficiency as a size-normalized quality metric identifying ligands that achieve potent binding through geometric complementarity rather than molecular bulk. Gaussian mixture analysis of the maximum eigenvalue distribution among strong binders reveals two distinct spectral modes corresponding to planar aromatic and three-dimensional sp3-rich scaffolds, confirmed by significant differences in fraction of sp3 carbons and aromatic ring counts ($p<{10}^{-8}$). As an intentionally ligand-centric framework, our approach complements rather than replaces protein-aware co-modelling architectures. This work establishes cellular sheaf theory as a principled framework for encoding molecular topology with statistically significant associations with binding affinity, providing interpretable geometric insights that are inaccessible to conventional molecular descriptors. Full article

Standard fringe-based structured-light processing estimates wrapped phase from phase-shifted sinusoidal images and commonly relies on phase unwrapping to obtain a globally consistent phase representation. In practical measurements, this approach may become unstable on reflective objects and under low or non-uniform illumination, where the recorded fringe signal is distorted and the recovered phase becomes unreliable. To address these limitations, we propose a correspondence extraction method based on subpixel peak localization performed directly on phase-domain images. The wrapped phase is transformed into absolute value phase profiles, $\Phi =|{\varphi }_w|$, whose local structure follows the projected fringe pattern and is less affected by object-dependent intensity variations. The proposed method reformulates correspondence extraction as a local signal-based estimation problem in the phase-domain, thereby reducing reliance on global phase-consistency constraints at the correspondence stage. A practical advantage observed in the evaluated examples is that the method remained usable in some regions where the phase became locally flat because of low modulation, saturation, or reflective surface effects. In such regions, conventional processing relies on sufficiently reliable phase gradients and subsequent unwrapping, whereas the proposed method uses local peak geometry in the transformed phase representation. In the implementation used here, Gray-code information is employed only for pixel-wise phase extension and reference indexing, not as a spatial phase-unwrapping mechanism. The method does not require machine learning models or training data and can be integrated as a correspondence analysis stage in practical structured-light systems. Full article

Extracting causal relations from complex dynamic systems has become an appealing topic for decades, especially for machine design engineering, industrial manufacturing, and equipment maintenance, which usually suffer from a large number of tangled relationships. Although many causality detection methods have been utilized, evaluating and choosing appropriate methods, and developing proper workflow remain challenges. In this paper, a causal analysis workflow designed to detect hidden patterns involved with mechanical mechanisms is presented. In particular, various causality measures are ensembled, enabling the search for refined causal mechanisms, the impact of constitutive law, and spatial distribution of causality from the entangled raw network. Based on numerical experiments, several beneficial conclusions can be drawn: Separating typical stages is necessary for a complex process; The constitutive property has a great impact on causal inference; The discrepancy of causality among different locations of monitor points mainly depends on whether it is near the fixed boundary, near to the load, or in contact with friction; Granger Causality is suitable for discovering linear dependencies among material, load, and geometry, while constraint-based and score-based algorithms excel in identifying nonlinear causality in metal plasticity, severe discontinuity in contact, impulsive dynamic load, or damping phenomenon. Full article

Urban planners increasingly require high-resolution thermal comfort maps to prioritize heat adaptation, yet validating the necessary microclimate models against standard field instruments remains methodologically fraught. This study establishes an integrated measurement–modeling framework applied to a study area in Strasbourg, France. First, we evaluate the radiative physics of the LASER/F model against net radiometer measurements at a specific sub-canopy location and against incoming shortwave radiation pyranometer records across three instrumentation sites. Results demonstrate high accuracy for longwave fluxes ($R^2>0.95$) but reveal that simplified tree geometry leads to condition-dependent shortwave discrepancies. Second, we quantify the systematic divergence between Mean Radiant Temperature derived from black globe measurements and six-directional simulations across seven sites. We analyze how these inevitable discrepancies, stemming mainly from geometric mismatch, propagate into the Universal Thermal Climate Index (UTCI), resulting in (71.5–75.5%) diurnal exact categorical agreement. Finally, spatial application of the model uncovers a “masked risk”: while temporal averaging suggests that 100% of the district remains safe (mean UTCI $<{32}^{\circ }\mathrm{C}$), duration-based analysis reveals that 72.8% of surfaces actually experience critical heat stress for over a quarter of the period. To address these hidden exposure risks, we propose a “Combined Risk Score” (CRS) that integrates thermal intensity and critical exposure duration on an absolute, dataset-independent scale, with a sensitivity analysis demonstrating that spatial risk prioritization is invariant to the intensity–duration weighting choice at the operational threshold. Full article