Search Results (30,019)

This study proposes a novel pneumatically driven mechanically prestressed rhombic bistable composite laminate with asymmetric cylindrical curvature, which exhibits two weakly-coupled cylindrical shapes where each shape is influenced by planform and geometry parameters. A reduced-order analytical model is developed to predict the laminate’s quasi-static equilibrium shapes and snap-through transitions of the laminate under pneumatic work loading, which is triggered by the internal pressure applied to the fluidic channels. A sensitivity study based on the model investigates the influence of key planform and geometric parameters (the internal angle α and aspect ratio E) on the laminate’s out-of-plane deflection and snap-through pressure. The results show that increasing α reduces the critical prestrain required to achieve bistability and amplifies the out-of-plane deflection, while excessive α may lead to monostable curvature. Variations in aspect ratio modify the coupling stiffness between orthogonal PEMC layers, thereby influencing the bistable domain and critical snap-through pressure. These findings provide methods for the design of bistable composite structures. Full article

Automatic Identification System (AIS) trajectories provide valuable spatiotemporal information for maritime route structure mining, but robust extraction of key route nodes remains difficult because raw data are noisy, turning behaviors are easily masked by local fluctuations, and conventional Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is sensitive to fixed parameters and ignores heading differences. To address these issues, this study proposes a key route node extraction framework based on multi-constraint turning-point identification and heading-aware adaptive DBSCAN (HA-DBSCAN). Raw AIS data are first cleaned, segmented, and compressed using a heading-aware Douglas–Peucker strategy to reduce redundancy while preserving geometric and directional characteristics. Valid turning points are then identified by jointly considering heading change rate, geometric curvature, and temporal stability. Finally, HA-DBSCAN integrates a heading-aware distance metric, adaptive neighborhood estimation, and density-aware MinPts optimization to cluster turning points and extract representative route nodes. Experiments using AIS data from the Ningbo–Zhoushan Port area retained 287,614 valid records and 754 continuous trajectory segments, from which 1710 turning points were identified. The proposed method generated 45 stable clusters with a noise ratio of 0.0450 and route coverage of 95.5%. These results indicate that, within the current study setting, the framework can distinguish crossing routes, adapt to heterogeneous traffic densities, and provide an interpretable intermediate layer for subsequent maritime route-structure modeling. Supplementary validation on the same AIS dataset further showed that, compared with DBSCAN, Ordering Points To Identify the Clustering Structure (OPTICS), and HDBSCAN baselines as well as several pipeline ablations, the full framework achieved a more balanced performance in terms of coverage, noise suppression, and avoidance of cluster over-fragmentation. Full article

This research aims to study the compressive behavior of concrete with partial replacement of fine aggregate by recycled rubber. In addition, the mechanical capacity of these concretes will be analyzed when reinforced by carbon fibers (CFRP) and basalt (BFRP) confinement. To carry out the work, 48 cylindrical test specimens were made, corresponding to 4 mixes, with different percentages of recycled rubber by volume (0%, 10%, 20%, and 30%). The compressive behavior of unreinforced concrete with and without recycled rubber, reinforced concrete made from concrete with and without recycled rubber previously taken to failure, and reinforced concrete with and without recycled rubber without prior failure were evaluated in order to assess the influence of concrete quality before placing the reinforcement. The results show that replacing fine aggregate with recycled rubber in concrete reduces its strength and stiffness, increasing its ductility, with the optimum replacement percentage being 10%. On the other hand, confining concrete with FRP (BFRP and CFRP) improves its strength and ductility compared to unconfined concrete, obtaining similar values regardless of the initial strength of the reinforcing concrete. Confining concrete with CFRP achieves strength improvements of 26% compared to reinforcement with BFRP. Full article

Active distribution networks require precise real-time monitoring and control despite measurement outliers and rapid load dynamics. Conventional robust estimators frequently fail to distinguish between transient measurement corruption and genuine physical state mutations, leading to estimation lag or erroneous control actions. To address this, we propose a resilient cyber–physical framework that jointly optimizes robust dynamic state estimation and collaborative voltage control. At the estimation layer, a novel Persistence-Based Robust Extended Kalman Filter (PB-REKF) is developed, which employs a temporal persistence counter to adaptively switch between Huber M-estimation for sporadic outlier suppression and covariance inflation for rapid tracking of persistent state mutations. At the control layer, a chance-constrained Second-Order Cone Programming (SOCP) strategy directly embeds the real-time posterior covariance from the PB-REKF into the voltage safety constraints, creating a data-quality-adaptive security buffer that provides a $95\%$ probabilistic voltage guarantee. Simulations on 5-bus and IEEE 33-bus systems demonstrate that the proposed framework achieves a $29.5\%$ reduction in global RMSE and a $72.8\%$ reduction in peak outlier-window estimation error relative to the standard EKF, while reducing the voltage violation rate from $8.8\%$ to $3.8\%$. The complete estimation and control pipeline requires $1.341$ ms per update step, confirming real-time feasibility. Full article

The nonlinear dynamic response of aerospace thin-walled structures in a post-buckling state under thermo-acoustic loads is critical for their design. This study investigates this phenomenon through integrated experimental and numerical approaches. Acoustic tests on thermally stressed flat plates yielded results in close agreement with finite element and reduced-order modal (FEM/ROM) simulations, with first-order frequency deviations within ±2 Hz and strain values of the same order of magnitude (10.7 µε vs. 9.5 µε at 50 °C). A key observation is the non-monotonic variation in the thermal modal frequency, which initially decreases then increases with the buckling coefficient, while dynamic strain data further validate the computational model. Comparative analysis of three Haynes 188 alloy geometries—flat plates, cylindrical shells, and spherical shells—reveals distinct behaviors rooted in their critical buckling temperatures (68.46 °C, 151.20 °C, and 698.28 °C, respectively): flat plates exhibit softening–hardening transitions with a frequency range of 491–624 Hz; cylindrical shells show irregular responses with a dramatic frequency drop from 1120 Hz to 360 Hz; and spherical shells maintain the highest stability and frequency range (1913–2109 Hz), governed by the buckling coefficient’s linear effect. Time-domain and probability density function (PDF) analyses elucidate the snap-through phenomena and the modulating roles of the buckling coefficient and sound pressure level (SPL). These findings underscore that geometric configuration and inherent stiffness are critical to post-buckling performance, providing a theoretical basis for designing aerospace components in extreme environments. Full article

Suppose that we have a statistical model with q unknown parameters w, and an estimate $\widehat{w}$, based on a sample of size n. A basic question is: what is the covariance of the estimate? The covariance is needed for the Central Limit Theorem (CLT). This gives a first approximation for the distribution of $\widehat{w}$. But what if $q_n=n$ increases with n? How fast can it increase and the CLT still hold? An answer has so far only been given for the sample mean. The same is true for the Edgeworth expansions. These are expansions in powers of $n^{-1/2}$ for the density and distribution of $\widehat{w}$. For fixed q, these expansions are important, as they show how small n can be for the CLT to apply. When it does, they can greatly improve the accuracy of the CLT. I give conditions that allow for the Edgeworth expansions to remain valid when $q_n=q$ increases with n. Earlier Edgeworth expansions when $q_n=q$ increases, have only been done for a sample mean, and only for a 2nd order Edgeworth expansion. In contrast, I consider a very large class of estimates, the class of non-lattice standard estimates. An estimate is said to be a standard estimate if its mean converges to its true value as n increases, and for $r\ge 1$, its rth order cumulants have magnitude $n^{1-r}$ and can be expanded in powers of $n^{-1}$. For this class of estimates, I show that the Edgeworth expansions hold if $q_n$ grows as a power of n less than $1/6.$ That is, I give these expansions in powers of $n^{-1/2}{q}_n^3$. This large class of estimates has a huge range of potential applications, as estimates of high dimension are common in nearly all areas of applied statistics. The most important type of standard estimate is when $\widehat{w}$ is a smooth function of a sample mean, of dimension p say. When either or both $q_n=q$ and $p_n=p$ increase with n, I give conditions on their growth for the Edgeworth expansions for $\widehat{w}$ to remain valid: the eighth power of p times the sixth power of q cannot grow as fast as n. This holds for fixed $q=q_n$ if $p_n$ grows less than a power of n less than $1/8$. This appears to be the first time when Edgeworth expansions have been given when not one, but two dimensions, are allowed to increase to ∞ with n. This gives two different pathways for allowing an increase in dimensionality. When $q=1$, I give 5th order Edgeworth-Cornish-Fisher expansions for the standardized distribution and its quantiles of any smooth function of a sample mean of dimension $p_n$, when $p_n$ is a power of n less than $1/2$. However for the special case when this function is linear, there is no restriction whatever on how fast $p_n$ can increase! If also the components of the sample mean are independent, then these expansions are in powers of ${\left(np\right)}^{-1/2}$. I also give a method that greatly reduces the number of terms needed for the 2nd and 3rd order terms in the Edgeworth expansions, that is, for the 1st and 2nd order corrections to the CLTs. I also extend these results to the case where $\widehat{w}\in R^q$ is a function of several independent sample means, each of dimension increasing with n, with total dimension p. Full article

With the large-scale construction of coastal high-speed railways, understanding the mechanical behavior of high-speed railway box girders under tsunami waves has become increasingly important. Existing studies on tsunami-induced forces on bridge girders have mainly focused on T-girders and plate-girders in highway bridges. In contrast, research on high-speed railway box girders, which are characterized by a significant height-to-width ratio, large cantilevers, and complex ancillary facilities on the girder top, remains relatively scarce, especially regarding its behavior under tsunami waves and the effects of lateral displacement on its dynamic response. In light of this, this study focuses on the investigation of the mechanical behavior of a single-track high-speed railway box girder under tsunami waves, and fifth-order solitary waves and dam-break waves are comparatively employed to simulate the typical unbroken and broken tsunami waves. The interaction between tsunami waves and the fixed railway box girder is numerically conducted, and the characteristics of the interaction process and the variation in maximum forces with girder clearance are thoroughly investigated. After that, the numerical interaction between tsunami waves and the laterally movable railway box girder is comparatively carried out, and the lateral displacement effects on the girder wave forces are exhaustively investigated. The results indicate that unbroken and broken tsunami waves exhibit distinctly different interaction processes with the box girder. With decreasing girder clearance, for the unbroken wave, the maximum horizontal and vertical forces occur when the girder bottom and the cantilever root descend to the initial water surface, respectively; for the broken wave, the horizontal and vertical forces simultaneously occur when the girder bottom nears the water surface with a small clearance. Lateral displacement can reduce wave forces on the girder, but the reduction is quite limited—remaining below 10% at the reference stiffness of an actual bearing. It validates that using a fixed girder model to estimate wave forces on an actual laterally movable girder is a slightly conservative and reasonable approach. This study provides further insight into wave forces acting on coastal high-speed railway box girders in tsunami-prone areas. Full article

A preliminary analysis of aircraft refueling using liquid hydrogen (LH2) for a future short–medium-range aircraft is presented. The focus is on how selected refueling parameters influence pressure buildup and the release of boil-off gas (BOG), in order to establishing guidelines towards efficient refueling. The flow physics uses a 0-D multi-phase lump model, which accounts for the effects of the injected LH2, BOG release, heat fluxes and phase changes. Refueling is controlled by volumetric compression during the filling, and relaxation afterwards. Mass-flow profile and refueling protocol have little influence on the amount of BOG vented (~1%), but control the duration of the process, with variations close to 50%. Low initial pressure can significantly reduce the amount of BOG. Full article

Mixed-scene holographic 3D display for film and television visual content presentation remains challenging because recorded digital holograms and computer-generated holograms (CGHs) are produced under different numerical and hardware constraints. Direct hologram superposition typically causes strong zero-order interference, diffraction efficiency degradation, and sampling pitch mismatch between the recording sensor and the replay panel, while conventional resizing reduces the effective replay aperture and narrows the available parallax. To address these issues, this paper proposes a zero-order-suppressed single-hologram fusion framework with parallax-preserving digital resizing. A recorded digital hologram is first processed by Gaussian high-pass filtering to suppress the dominant zero-order component, then resampled to match the LCOS replay pitch, and finally normalized and fused with a CGH generated through bipolar intensity encoding. On this basis, two resizing routes are developed: a spatial-domain method for aperture-preserving whole-scene scaling and a frequency-domain method for object-selective scaling and translation. Optical validation on a three-channel LCOS prototype shows that the quantitative diffraction efficiency analysis predicts an increase from approximately 10.1% to 20.05% per reconstructed object for the two-hologram fusion case, and the revised experimental results are consistent with this improvement trend. The experiments further verify replay scaling at multiple factors, the selective manipulation of physical and virtual objects, mixed-scene color replay, and occlusion-consistent depth ordering. Together with the distortion analysis, these results demonstrate improved replay visibility after fusion while maintaining geometric controllability and effective replay aperture. By relying on hologram-domain preprocessing and resizing rather than full mixed-scene recomputation, the proposed method also reduces computational burden. The study therefore provides an efficient and controllable mixed-scene holographic replay framework for visually enriched film and television content presentation, although its depth applicability remains bounded and dedicated real-time timing benchmarks are left for future work. Full article

Predicting the maneuverability of ships equipped with twin azimuth thrusters remains challenging due to their complex hydrodynamic interactions. This study develops an integrated framework that combines Computational Fluid Dynamics (CFD) with an enhanced Manoeuvring Mathematical Group (MMG) Model. Using the platform supply vessel Hai Yang Shi You 661 as a case study, all requisite hydrodynamic derivatives and propeller coefficients were efficiently obtained through CFD-based captive model tests, including oblique towing and Planar Motion Mechanism tests, conducted in STAR-CCM+ 2206. A core contribution of this work is the systematic evaluation of how hydrodynamic model fidelity affects prediction accuracy. Numerical turning circle simulations were executed with three models of increasing complexity: one with only linear derivatives, a second incorporating nonlinear higher-order terms, and a third, full model that additionally includes nonlinear velocity coupling terms. The results, rigorously validated against full-scale trial data, demonstrate that while the basic CFD-MMG approach is feasible, the inclusion of nonlinear coupling terms is critical for achieving accurate predictions in large-amplitude maneuvers. This enhancement reduced the maximum error in tactical diameter prediction from over 25% to approximately 11.8%. Consequently, this study provides a validated and cost-effective framework for maneuvering the prediction of azimuth-thruster vessels and offers clear, quantitative guidance on the necessary level of model complexity for practical engineering applications. Full article

Underwater gated time-correlated single-photon-counting (TCSPC) LiDAR is advantageous when weak target echoes coexist with strong backscatter. However, under the first-photon-triggering and SPAD dead-time mechanism, the estimated time of flight becomes dependent on the return strength, thereby producing a range walk error (RWE). This paper develops a condition-calibrated correction framework for accumulated-histogram underwater ranging in the low-photon regime. A non-homogeneous Poisson first-arrival model that jointly includes gate-limited signal photons and in-gate background triggering yields a computable expression for the total trigger probability and the conditional first-arrival time. A first-order expansion around $N_{pe}\approx 0$ leads to an approximately linear RWE–$N_{pe}$ relation under the present system–water condition. A density-based signal-window localization method and a noise-occlusion-compensated estimator of $N_{pe}$ are combined with reference-plane differential calibration. Experiments in a 10 m clear-freshwater tank at 9.11 m show that the mean absolute error is reduced from 39.205 mm to 2.130 mm, corresponding to a 94.57% improvement. Compared with a quadratic model used under higher-photon conditions, the proposed linear model yields an order-of-magnitude smaller residual error in the low-photon region ($N_{pe}<1.6$). Full article

CuIn₅Se₈ is reported as a remarkable copper-deficient layer that contains ordered vacancy compounds (OVCs) for high-efficiency chalcopyrite-based solar cells; however, the understanding of its carrier characteristics has remained limited. OVCs could naturally form on the surface of chalcopyrite absorber. In this study, the carrier dynamics characteristics of OVCs were investigated by constructing a junction consisting of chalcopyrite absorber and CdS buffer layer. At first, the band structure of CuIn₅Se₈ was studied to determine the bandgap properties. Then, thermodynamic stability, defect formation energy, defects and carrier concentration, defect transition energy level of CuIn₅Se₈ and its Cd doping state (caused by CdS) were comparatively studied. The results suggest that Cd doping has different effects on the defect and carrier characteristics of OVCs with various chemical potentials. However, the OVC always remains n-type under the whole thermodynamically stable region, with contribution from the hallow-level In_Cu donor defect. Finally, the OVC’s carrier dynamics characteristics were assessed using the collected defect and carrier data. It is indicated that the OVC layer may contribute to the formation of a p-n homojunction in solar cells. Under selenium-rich conditions, the OVC layer increases the carrier density on the n-type side of p-n junction nearly 30-fold, which helps reduce the difference in carrier density and minority current density between two sides of the p-n junction. The conversion efficiency of the solar cell with OVC shows a 7.25% improvement when compared to the control. The distinct behavior of OVCs may serve as a valuable reference for the creation or improvement of a related functional film layer or device. Full article

The automatic classification of ISUP (International Society of Urological Pathology) grade groups in prostate histopathological images remains challenging due to the high similarity between adjacent classes, class imbalance, and label noise. In this work, we propose a deep learning pipeline based on EfficientNet convolutional neural networks combined with a hybrid loss function that integrates ordinal regression and Focal Loss to better capture the ordered nature of ISUP grades. A noise-filtering strategy based on the entropy of predictions from multiple EfficientNet models was first applied to identify and remove high-uncertainty samples from the training set. The problem was then reformulated as an ordinal regression task to explicitly model the hierarchical relationship among grades. Experiments conducted on the PANDA dataset demonstrate that removing noisy samples improved performance from $\kappa =0.826$ to $\kappa =0.833$. Incorporating ordinal loss further increased performance to $\kappa =0.851$. The best configuration, combining ordinal regression and Focal Loss, achieved $\kappa =0.857$ and an accuracy of $0.669$, while reducing severe misclassifications and concentrating errors among adjacent classes. These results indicate that explicitly modeling ordinal structure and mitigating label noise are effective strategies for improving prostate cancer grading systems. Full article

We construct and analyze a family of support-defined Brauer-type configurations canonically associated with the Boolean geometry underlying the Grassmann algebra. The construction is governed by an x-support map on monomial labels, which identifies the vertex set with the Boolean lattice $\mathcal{P}\left(\right[n\left]\right)$. This identification yields a Boolean support quiver isomorphic to the directed Hasse diagram of $\mathcal{P}\left(\right[n\left]\right)$, equivalently, to an oriented hypercube. We then equip the family with a canonical cyclic ordering at each vertex and obtain a genuine connected reduced Brauer configuration in the standard sense, together with its associated Brauer configuration algebra and its standard Brauer quiver. A ghost-variable mechanism is introduced to obtain a connected realization without altering any support-controlled invariants. We prove that polygon membership, valencies, multiplicities, Boolean stratification, and the support quiver are invariant under support-preserving ghost relabelings. We also give an explicit description of the standard Brauer quiver and show that it is different from the Boolean support quiver. On the algebraic side, we derive closed formulas for the center dimension, the algebra dimension, and the normalization constant of the induced weighted distribution. On the probabilistic side, we distinguish the vertex entropy from the layer entropy, establish an exact decomposition of the former by Hamming layers, and show that the layer distribution is asymptotically concentrated on the middle layers, while extremal vertices and any fixed maximal path contribute a negligible fraction of the total weight. As a consequence, the layer entropy satisfies a logarithmic asymptotic law. We also investigate geometric consequences of the Boolean model transported through the support identification. Coordinate projections produce a rigidity phenomenon for antipodal pairs, providing a combinatorial analogue of Greenberger–Horne–Zeilinger (GHZ)-type fragility, whereas the first Boolean layer exhibits a persistence property analogous to W-type robustness. Together, these results exhibit a concrete bridge between Grassmann combinatorics, Brauer configuration theory, hypercube geometry, and entropy asymptotics. Full article

We study a modified-degenerate version of the $W_{\alpha ,\beta ,\nu }$-factorial and the associated exponential, trigonometric, and hyperbolic families obtained by replacing the Euler gamma function with the modified-degenerate gamma function ${\Gamma }_{\lambda }^{*}$, where $\lambda \in (0,1)$. A main conclusion of this paper is that this construction does not generate a genuinely new transcendental family. Indeed, since ${\Gamma }_{\lambda }^{*}\left(s\right)=b_{\lambda }^s\Gamma \left(s\right),b_{\lambda }={\displaystyle \frac{\lambda }{log(1+\lambda )}},$ all modified-degenerate W-functions reduce to exact rescalings of their non-degenerate counterparts. The novelty of the present work is therefore operational rather than structural. We formulate this transport principle explicitly, derive the corresponding modified-degenerate Laplace-transform identities directly in the spectral variable s, establish the induced convolution rule, and obtain first-order asymptotic expansions as $\lambda \to 0^{+}$. We further show that the associated W-derivative is a formal coefficient-shift operator, and conjugate it to the non-degenerate one under the scaling map. As an application, we present a complete Volterra integral-equation example with polynomial memory, including an explicit resolvent representation for the case $m=1$, together with convergence and residual-error checks supporting the numerical illustrations. Full article