Search Results (4,403)

Water Alternating Gas (WAG) injection is a well-established enhanced oil recovery technique that improves sweep efficiency by combining the favorable displacement characteristics of waterflooding and gas injection. This work presents a sequential Picard–Newton formulation for simulating three-phase flow under WAG conditions in heterogeneous petroleum reservoirs. The mathematical model addresses slightly compressible, immiscible oil, water, and gas phases under constant-temperature conditions, with the governing equations discretized in space and time using the finite volume method. Reservoir heterogeneity is represented through geostatistical permeability fields generated by Sequential Gaussian Simulation, capturing the spatial correlations and anisotropy characteristic of subsurface formations. The methodology is applied to investigate WAG performance in heterogeneous reservoir models with mean permeabilities of 100, 200, and 400 × 10${}^{-15}$ m${}^2$ under identical 1:1 injection ratios. The numerical results successfully reproduce the cyclic saturation and production behavior characteristic of WAG processes. Comparative analysis reveals that higher permeability enhances injectivity and cumulative recovery but accelerates gas breakthrough and, in the highest-permeability case, water breakthrough, as well as production decline, illustrating the trade-off between displacement efficiency and sweep control. These findings demonstrate that the proposed framework provides an efficient and physically consistent tool for evaluating WAG strategies in heterogeneous reservoirs, with potential application to field-scale optimization of advanced recovery operations. Full article

Time remains one of the most elusive concepts in physics, lying at the intersection of quantum mechanics, relativity, and thermodynamics. This work proposes a reformulation in which time arises as a local informational field rather than as a universal coordinate. Temporal direction is identified with gradients in stored information, linking geometry and entropy through an informational potential that generates both curvature and the arrow of time. The resulting field $T^a\left(x\right)={\partial }^a{S}_{\mathrm{info}}\left(x\right)$ defines causal order and temporal flow through local information exchange, unifying dynamical evolution and entropic asymmetry within a single framework. The formulation preserves general relativity in the macroscopic limit while extending its validity to microscopic regimes where information dynamics supersede geometric structure. It thus offers a coherent physical basis for temporal asymmetry, a bridge between quantum and gravitational descriptions, and a platform for simulating time as an observable field. Full article

We investigated diffusion of thin and thick nanorods with varying lengths and rigidities in cross-linked polymer networks using coarse-grained molecular dynamics (CGMD) simulations. Our results show that the translational diffusion of nanorods slows down with power scaling laws as their length increases, exhibiting a non-monotonic dependence on rigidity of thin nanorods, and decreases with the rigidity of thick nanorods. The sub-diffusion of nanorods is observed at short time scales, which becomes more pronounced for rigid nanorods. The nanorods show anisotropic diffusion behavior with favoring motion along their major axes in cross-linked networks, and the anisotropy enhances by increasing either rigidity or length of nanorods, especially for thick nanorods. The sub-diffusion behavior of nanorods is primarily due to the strong heterogeneity of motions perpendicular to major axes of nanorods, and the time scales of this heterogeneous diffusion increase with the length and rigidity of nanorods. In rotational dynamics, nanorods with higher rigidity rotate more slowly, and the effect is more evident in longer nanorods. The rotational diffusion coefficient follows a power scaling law with the rigidity of nanorods, when the effective length of a nanorod exceeds the mesh size of cross-linked network. The rotations of nanorods also display heterogeneous dynamics, in which the time scale of heterogeneous rotation increase with rigidity, and such heterogeneity is more pronounced in softer nanorods. Overall, our work elucidates the microscopic mechanisms governing both translational and rotational diffusion of nanorods in cross-linked networks. Full article

Objectives: Spinal cord injury (SCI) disrupts the microstructure of the spinal cord, triggers reorganization of the brain network, and causes motor deficits. However, the temporal dynamics and interrelationships of these alterations remain unclear. Methods: Eight monkeys underwent spinal cord hemisection and were randomly assigned to either the SCI-only group or the treatment group that received neurotrophin-3-chitosan implants. Longitudinal brain structural/resting-state magnetic resonance imaging and spinal cord diffusion tensor imaging (DTI) were conducted. Concurrently, hindlimb motor function was assessed. The brain network topology was characterized through graph theory. The generalized additive mixed model (GAMM) was employed to analyze the longitudinal trajectories of network metrics, while the linear mixed-effects model (LMM) was used to evaluate the moderating effect of treatment on correlations between network metrics and motor/DTI parameters. Results: The SCI-only group exhibited sustained functional network segregation, aberrant structural topology, and lower fractional anisotropy (FA). These findings collectively reflect chronic maladaptive plasticity. In the treatment group, the therapy not only enhanced white matter integrity, reflected by increased FA values, but also reduced the clustering coefficient (Cp) in brain structural network, indicating a shift away from maladaptive segregation. Critically, the LMMs further revealed that treatment moderated the pathological correlations between global efficiency (Eg), local efficiency, Cp, and locomotor parameters. Moreover, spinal FA exerted a significant main effect on Eg of brain functional networks. Conclusions: These findings suggest that treatment-induced brain reorganization underlies motor function following SCI, and progressive brain reorganization correlates with changes in spinal cord microstructure, revealing a systems-level mechanism of neural repair. Full article

The mechanical and durability performance of cementitious materials is fundamentally governed by the symmetry, anisotropy, and hierarchical organization of their microstructures. Conventional experimental characterization—based on imaging, spectroscopy, and physical testing—often struggles to capture these multiscale spatial patterns and their nonlinear correlations with macroscopic performance. Recent advances in machine learning (ML) provide unprecedented opportunities to interpret structural symmetry and anisotropy through data-driven analytics, computer vision, and physics-informed models. Furthermore, we summarize cases where symmetry-informed descriptors improve performance prediction accuracy in fiber- and nano-modified composites, demonstrating that ML-based symmetry analysis can substantially complement the limitations of conventional experimental-based characterization. We confirm that image-based models such as CNN and U-Net quantify the directionality and connectivity of pores and cracks, and that physically informative neural networks (PINNs) and heterogeneous data-based models enhance physical consistency and computational efficiency compared to conventional FEM and CFD. Finally, we present the conceptual and methodological foundation for developing AI-based microstructural symmetry analysis, aiming to go beyond simple prediction and establish a conceptual foundation for AI-driven cement design based on microstructure–performance causality. Full article

We investigate a non-Hermitian two-spin XY model driven by alternating real and imaginary transverse fields and derive an explicit analytic formula for the ground-state entanglement negativity. This provides a systematic analytic characterization of how ground-state entanglement behaves across PT-symmetry breaking in a non-Hermitian spin dimer. In the PT-symmetric regime, the anisotropy $\gamma$ enhances entanglement, whereas the real field h₀ suppresses it; in the PT-broken regime dominated by $\left|{\phi }_3\right.⟩$, the negativity decreases monotonically with the imaginary field ${\eta }_0$. Moreover, the first derivative of the negativity exhibits a cusp-type non-analyticity at the exceptional point (EP), consistent with the ground-state phase boundary and revealing a direct correspondence between entanglement transitions and exceptional-point physics. To facilitate implementation in integrated quantum photonics, we map $\left(h_0,{\eta }_0,\gamma \right)$ onto the device parameters $\left(\Delta \beta ,g,\kappa \right)$ of a PT-symmetric directional coupler and propose a two-qubit quantum state tomography readout based on local Pauli measurements, thereby offering a concrete entanglement-based probe of exceptional-point signatures in a realistic photonic platform. Within this model, we identify parameter regimes for observing this signature: a cusp feature is expected near $\Delta \beta \approx 0$ and $g\approx \kappa ,$ which remains observable under small detuning and moderate loss mismatch. These results offer a testable avenue for entanglement-based probing of PT-symmetry breaking and may inform device characterization and quantitative assessment in integrated quantum photonics. These combined advances provide both analytical insight into non-Hermitian entanglement structure and a feasible route toward experimentally diagnosing PT-symmetry breaking using entanglement. Full article

The advancement of polymeric materials for orthopedic applications has enabled the development of lightweight, adaptable structures that support patient-specific solutions. This study focuses on the design, fabrication, and mechanical characterization of additively manufactured (AM) polymeric polylactic acid (PLA) components produced via Material Extrusion (MEX), commonly known as Fused Filament Fabrication (FFF). By optimizing geometric configurations and process parameters, these structures demonstrate enhanced flexibility, energy absorption, and load distribution, making them well-suited for orthopedic products and assistive devices. A comprehensive mechanical testing campaign was conducted to evaluate the elasticity, ductility, and strength of FFF-fabricated samples under tensile and three-point bending loads. Key process parameters, including nozzle diameter, layer thickness, and printing orientation, were systematically varied, and their influence on mechanical performance was recorded. The results reveal that these parameters affect mechanical properties in a complex, interdependent manner. To better understand these relationships, an automated routine was developed to calculate the experimental mechanical response, specifically, stiffness and strength. This methodology enables an automated evaluation of the output, considering parameter ranges for future applications. The outcome of the analysis of variance (ANOVA) of the experimental investigation reveals that the printing orientation has a strong impact on the mechanical anisotropy in FFF, while layer thickness and nozzle diameter demonstrate moderate-to-weak importance. Thereafter, the experimental findings were applied on an innovative orthopedic wrist splint design to be fabricated by means of FFF. The most suitable mechanical properties were selected to test the mechanical response of the designed components under operational bending loading by means of linear elastic finite element (FE) analysis. The computational results indicated the importance of employing the actual mechanical properties derived from the applied printing process parameters compared to data sheet values. Hereby, an additional parameter to adjust the mechanical response is the product’s design topology. Finally, this framework lays the foundation for future training of neural networks to optimize specific mechanical responses, reducing reliance on conventional trial-and-error processes and improving the balance between orthopedic product quality and manufacturing efficiency. Full article

Background/Objectives: Idiopathic intracranial hypertension (IIH) is an uncommon but clinically important cause of elevated intracranial pressure in children. Conventional MRI findings such as perioptic subarachnoid space (SAS) distension and posterior globe flattening are helpful but may lack sensitivity or specificity in certain cases. Diffusion tensor imaging (DTI), which quantifies white matter microstructure through metrics such as fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), offers additional diagnostic potential, yet its role in pediatric IIH remains insufficiently defined. Methods: This retrospective case–control study included 26 pediatric patients with IIH and 26 age- and sex-matched controls who underwent brain MRI with DTI between 2010 and 2025. DTI parameters were measured in major white matter tracts, and conventional MRI findings associated with raised intracranial pressure were recorded. Associations between DTI metrics and conventional imaging markers were analyzed using standardized statistical tests. Results: Children with IIH demonstrated significantly reduced FA and increased MD and RD values in several key white matter regions, particularly within the optic radiation, splenium of the corpus callosum, and posterior limb of the internal capsule. FA values showed a negative correlation with perioptic SAS width, while RD and MD were positively correlated with posterior globe flattening and empty sella grade. Receiver operating characteristic analysis identified FA in the optic radiation as the strongest discriminator between IIH and controls (AUC = 0.83). Inter-observer reliability for FA measurements was excellent (ICC = 0.91). Conclusions: Pediatric IIH appears to be associated with pressure-related microstructural alterations in white matter, detectable through DTI. Among the diffusion metrics, FA demonstrated the strongest diagnostic potential and may serve as a complementary tool to conventional MRI. Validation in larger, prospective pediatric cohorts is required to establish its clinical utility. Full article

A roller straightening process of a pure magnesium strip, accompanied by alternating elastic-plastic deformation, was performed through one and three passes, where one pass corresponded to 19 bending events. It was discovered that roller straightening leads to the appearance of a kink in the specimen’s tensile stress–strain curve as well as an almost twofold decrease in the yield stress. This effect was observed only on longitudinal specimens. The conducted EBSD analysis confirmed the previously stated hypothesis about the influence of twinning on the change in the shape of the roller-straightened magnesium alloy specimen’s stress–strain curve. The tensile twins {$10\overline{1}2$} formed during roller straightening facilitate the detwinning process during subsequent tensile deformation, which, along with the basal sliding, is the reason for the decrease in yield stress. The scaling factor of the tensile specimens was investigated. Full article

Joints and other discontinuities in rock masses cause overbreak, underbreak, and instability during tunnel blasting. This paper reviews recent advances in damage control for jointed rock tunnels and validates key findings through numerical simulations. At the microscale, joints affect stress wave propagation, energy distribution, and crack growth patterns. We used ANSYS/LS-DYNA 19.0 to simulate 16 parametric cases and quantify the effects of joint geometry on blasting response. Results show that joint-to-borehole distance is the primary factor controlling damage distribution. A joint dip angle of 45° produces the most severe damage anisotropy, with cracks propagating preferentially along the joint plane. A three-dimensional tunnel model was then developed to assess water-pressure blasting. Compared with conventional methods, water-pressure blasting reduces damage depth by 20.4% and peak particle velocity by 57.6% in jointed rock. The paper also discusses parameter optimization methods, intelligent evaluation techniques, and dynamic control strategies. Engineering recommendations are provided for different geological conditions, including horizontally layered rock, inclined joints, and deep high-stress environments. This work offers both theoretical insights and practical guidance for precision blasting in jointed rock tunnels. Full article

Accurate deformation monitoring is essential for ensuring the stability of deep vertical shafts. In this study, a temperature-compensated fiber Bragg grating (FBG) sensing system was deployed in the 882 m deep Guotun Coal Mine shaft to measure circumferential and vertical strains at six depths. A site-specific mechanical model integrating stratigraphy, dual-layer concrete lining, and the influence radius was developed to analyze shaft wall stresses. The monitoring results reveal pronounced spatial anisotropy, with circumferential compressive and tensile strains at deeper levels nearly twice those at shallow levels. Strain variation also increases over time, reflecting the combined effects of groundwater fluctuations and overburden consolidation. The stresses inferred from measured strains agree well with the analytical solution in both magnitude and depth-dependent trend, with deviations remaining within a reasonable engineering margin. All stresses are below the strength limits of the C70/C50 concrete lining, confirming that the shaft is in a safe stress state. The proposed monitoring–analysis framework provides a reliable basis for evaluating shaft wall behavior under complex hydrogeological conditions. Full article

To advance “bamboo-as-plastic-substitute” initiatives and the sustainable use of furniture materials, this study investigates flattened bamboo sheets by determining their principal-direction elastic constants and evaluating two common furniture T-joints—dowel-jointed panel-type and right-angle mortise-and-tenon frame-type—through tensile and bending load-bearing tests alongside finite element (FE) comparisons. The results show a pronounced anisotropy, with the longitudinal elastic modulus markedly higher than in other directions. At the joint level, the average ultimate load-bearing capacities were 4.06 kN (panel-type tension), 3.70 kN (frame-type tension), 0.264 kN (panel-type bending), and 0.589 kN (frame-type bending). Under identical structural configurations and boundary conditions, the tensile and bending capacities of flattened bamboo sheets were comparable to or exceeded those of the comparator materials (MDF, cherry wood, bamboo-based composites), and failures predominantly occurred in the adhesive layer rather than the bamboo substrate. Across four representative cases, FE predictions achieved a mean absolute percentage error (MAPE) of 6.5% with a maximum relative error of 12.5%; the regression correlation was R² ≈ 0.999 based on four paired observations, which should be interpreted with caution due to the small sample size. The study validates that FE models driven by experimentally measured anisotropic parameters can effectively reproduce the mechanical response of flattened bamboo T-joints, providing a basis for structural design, lightweighting, and parameter optimization in furniture applications. Further work should characterize adhesive systems, environmental durability, and interfacial failure mechanisms to enhance the model’s general applicability. Full article

Although the dynamic response of orthotropic materials under uniaxial impact loading has been extensively studied, their behavior under multiaxial stress states, which more accurately represent real-world blast and impact scenarios, has received limited attention. To address this gap, this study employed a self-developed biaxial impact testing apparatus to systematically investigate the dynamic mechanical behavior of beech wood, a typical orthotropic material, under three biaxial loading configurations: radial-tangential, radial-longitudinal, and tangential-longitudinal. By combining theoretical derivation with experimental data, it systematically examines stress wave propagation characteristics, strain rate effects, and anisotropy evolution under different loading paths. The results reveal that beech wood exhibits significantly distinct dynamic responses along different material orientations, with a consistent strength hierarchy: longitudinal > radial > tangential. Biaxial loading notably enhances the equivalent stress–strain response and alters the deformation mechanisms and energy absorption behavior. Furthermore, lateral confinement and multiaxial stress coupling are identified as critical factors influencing the dynamic performance. This study provides the first systematic revelation of the strain rate strengthening mechanisms and wave propagation characteristics of orthotropic materials from the perspective of multiaxial dynamic loading, thereby offering theoretical and experimental foundations for developing advanced dynamic constitutive models suitable for complex impact conditions. These findings provide important guidance for the design and evaluation of lightweight impact-resistant structures in fields such as aerospace and protective engineering. Full article

The research methodology involved creating a 3D sample model that featured both flat and cylindrical surfaces inclined at angles ranging from 0° to 90° relative to the XY plane. The study investigated the surface topography of additively manufactured samples produced using various technologies, including Fused Filament Fabrication (FFF), masked Stereolithography (mSLA), PolyJet (PJ), and Selective Laser Sintering (SLS). The focus was on how material type, print angle, and measurement location influenced the results. The materials used in the study included PLA, PETG, acrylic resins, PA2200, and VeroClear. Due to the optical properties of the materials used, measurements were carried out on replicas that were prepared using a RepliSet F5 silicone compound from Struers. Consequently, a methodology was developed for measuring surface roughness using the Alicona microscope based on these replicas. A 10× objective lens was used during the measurements, and the pixel size was 0.88 µm × 0.88 µm. Each time, an area of approximately 1 mm × 4 mm was measured. The lowest roughness values were observed for mSLA samples (Sa = 6.72–8.54 µm, Spk + Sk + Svk = 33.36–42.16 µm), whereas SLS exhibited the highest roughness (Sa = 27.86 µm, Spk + Sk + Svk = 183.79 µm). PJ samples exhibited intermediate roughness with significant anisotropy (Sa = 11.65 µm, Spk + Sk + Svk = 72.1 µm), which was strongly influenced by the print angle. FFF surfaces showed directional patterns and layer-dependent roughness, with the Sa parameter being the same (12.44 µm) for both PETG and PLA materials. The steepest slopes were observed for SLS surfaces (Sdq = 7.67), while mSLA exhibited the flattest microstructure (Sdq = 0.48–0.89). Statistical analysis confirmed that material type significantly influenced topography in mSLA, while print angle strongly affected PJ and FFF (although for FFF, further studies would be beneficial). The results of the research conducted can be used to develop a methodology for optimizing the printing process to achieve the required geometric surface structure. Full article

Synthetic Aperture Radar (SAR) has been widely applied for rice monitoring, especially in cloud-prone areas, due to its ability to penetrate clouds. However, only limited methods were developed to monitor separately irrigated rice and rainfed rice ecosystems. This study demonstrated the use of multi-temporal polarimetric dual-polarization (dual-pol) SAR (Sentinel-1B and ALOS PALSAR-2) data to monitor and discriminate the irrigated and favorable rainfed rice ecosystems in the province of Iloilo, Philippines. Key polarimetric parameters derived from H–A–α and model-based dual-pol decomposition were analyzed to characterize the rice phenology of both ecosystems. Segmented regression was performed to detect breakpoints corresponding to changes in rice phenology within each ecosystem and used to identify the parameters to use for classification. Based on the results, Sentinel-1B polarimetric parameters (entropy, anisotropy, and alpha) can capture the phenological dynamics, whereas ALOS2 polarimetric parameters were more sensitive to water conditions, as reflected in span and volume scattering. Furthermore, irrigated rice exhibited more stable and predictable scattering patterns than favorable rainfed rice. Using the Random Forest classifier, various combinations of backscatter and polarimetric parameters from Sentinel-1B and ALOS2 were tested to discriminate between the two ecosystems. The highest classification accuracy (81.81% overall accuracy; Kappa = 0.6345) was achieved using the combined backscatter (S1B VH, ALOS2 HH, and HV) and polarimetric parameters from both sensors. The results demonstrated that polarimetric parameters effectively capture phenological stages and associated scattering mechanisms, with the integration of Sentinel-1B and ALOS2 data improving the discrimination of irrigated and favorable rainfed rice systems. Full article