Search Results (67)

The chiral nonlinear Schrödinger equation (CNLSE) serves as a simplified model for characterizing edge states in the fractional quantum Hall effect. In this paper, we leverage the generalization and parameter inversion capabilities of physics-informed neural networks (PINNs) to investigate both forward and inverse problems of 1D and 2D CNLSEs. Specifically, a hybrid optimization strategy incorporating exponential learning rate decay is proposed to reconstruct data-driven solutions, including bright soliton for the 1D case and bright, dark soliton as well as periodic solutions for the 2D case. Moreover, we conduct a comprehensive discussion on varying parameter configurations derived from the equations and their corresponding solutions to evaluate the adaptability of the PINNs framework. The effects of residual points, network architectures, and weight settings are additionally examined. For the inverse problems, the coefficients of 1D and 2D CNLSEs are successfully identified using soliton solution data, and several factors that can impact the robustness of the proposed model, such as noise interference, time range, and observation moment are explored as well. Numerical experiments highlight the remarkable efficacy of PINNs in solution reconstruction and coefficient identification while revealing that observational noise exerts a more pronounced influence on accuracy compared to boundary perturbations. Our research offers new insights into simulating dynamics and discovering parameters of nonlinear chiral systems with deep learning. Full article

To characterize a phenomenological model of a mechanical oscillator, it is important to know the properties of the envelope of the three main physical motion variables: deviation from equilibrium, velocity, and acceleration. Experimental data show that friction forces restrict the shape of these functions. A linear, exponential, or more abrupt decay can be observed depending on the different physical systems and conditions. This paper aimed to contribute to clarifying the role that some types of friction forces play in these shapes. Three types of friction—constant sliding friction, pressure drag proportional to the square of velocity, and friction drag proportional to velocity—were considered to characterize the line connecting the maxima and minima of displacement for a generic mechanical harmonic oscillator. The ordinary differential equation (ODE), describing the harmonic oscillator simultaneously containing the three types of dissipative forces (constant, viscous, and quadratic), was numerically solved to obtain energy dissipation, and the extrema of both displacement and velocity. The differential equation ruling the behavior of the amplitude, as a function of the friction force coefficients, was obtained from energy considerations. Solving this equation, we obtained analytical functions, parametrized by the force coefficients that describe the oscillator tail. A comparison between these functions and the predicted oscillator ODE extrema was made, and the results were in agreement for all the situations tested. Information from the velocity extrema and nulls was enough to obtain a second function that rules completely the ODE solution. The correlations obtained allow for the reverse operation: from the identified extremum data, it was possible to identify univocally the three friction coefficients fitting used in the model. Motion equations were solved, and some physical properties, namely energy conservation and work of friction forces, were revisited. Full article

Shape-sensing optical fibers have become increasingly important in applications requiring flexible navigation, spatial awareness, and deformation monitoring. Fiber Bragg Grating (FBG) sensors inscribed in multi-core optical fibers have been democratized over the years and nowadays offer a compact and robust platform for shape reconstruction. In this work, we propose a novel, computationally efficient method for determining the 3D tip position of a bent multi-core FBG-based optical fiber using a second-order polynomial approximation of the fiber’s shape. The method begins with a calibration procedure, where polynomial coefficients are fitted for known bend configurations and subsequently modeled as a function of curvature using exponential decay functions. This allows for real-time estimation of the fiber tip position from curvature measurements alone, with no need for iterative numerical solutions or high processing power. The method was validated using miniaturized test structures and achieved sub-millimeter accuracy (<0.1 mm) over a 4.5 mm displacement range. Its simplicity and accuracy make it suitable for embedded or edge-computing applications in confined navigation, structural inspection, and medical robotics. Full article

Ultraviolet (UV) radiation can be used to inactivate microorganisms, with upper-room UV germicidal irradiation (UR-UVGI) representing a promising approach. This study investigated the inactivation of the airborne surrogate virus Phi6 by a UR-UVGI system based on light-emitting diodes (LEDs) in a realistic test setup. Two test scenarios were used, one with continuous Phi6 release, simulating a source located in the room and leading to a dynamic equilibrium, and the second simulating a situation in which the source has left the room and an exponential decay is evaluated. The “Incremental Evaluation Model” was adapted and used to evaluate the dynamic equilibrium measurement. At a position in the breathing direction 5 m away from the Phi6 source, the loss coefficient (air exchange rate) was 25 h⁻¹ in the first scenario and 30 h⁻¹ in the second. These results show that UR-UVGI systems can effectively inactivate microorganisms. However, at 1 m distance from the Phi6 source perpendicular to the breathing direction, only minimal inactivation was observed due to short-circuit airflow. At this position, the loss coefficient was <2 h⁻¹ in the first scenario and 17 h⁻¹ in the second scenario, indicating that short-circuit airflows can only be detected by dynamic equilibrium measurements. Full article

The kinetics of Br-atom reactions with C₂H₄S and ClNO were studied as a function of temperature at a total pressure of 2 Torr of helium using a discharge–flow system combined with mass spectrometry: Br + C₂H₄S → SBr + C₂H₄ (1) and Br + ClNO →BrCl + NO (2). The rate constant of reaction (1) was determined at T = 340–920 K by absolute measurements under pseudo-first-order conditions, either by monitoring the kinetics of Br-atom or C₂H₄S consumption in excess of C₂H₄S or of Br atoms, respectively, and by using a relative rate method: k₁ = (6.6 ± 0.7) × 10⁻¹¹ exp(−(2946 ± 60)/T) cm³molecule⁻¹s⁻¹ (where the uncertainties represent the precision at the 2σ level, the estimated total uncertainty on k₁ being 15% at all temperatures). The rate coefficient of reaction (2), determined either from the kinetics of the formation of the reaction product, BrCl, or from the decays of Br-atoms in an excess of ClNO, showed non-Arrhenius behavior, being practically independent of temperature below 400 K and increasing significantly at temperatures above 500 K. The measured rate constant is well reproduced by a sum of two exponential functions: k₂ = 1.2 × 10⁻¹¹ exp(−19/T) + 8.0 × 10⁻¹¹ exp(−1734/T) cm³ molecule⁻¹ s⁻¹ (with an estimated overall temperature-independent uncertainty of 15%) at T = 225–960 K. Full article

This research presents a detailed numerical modeling study focused on estimating the concentration of microplastics (MPs) in freshwater ecosystems. This research covers three lakes (Kopa, Zerendinskoye, and Borovoe) and the Yesil River, applying differential equations to model the spatial distribution and seasonal variations in MP concentrations. The methodology integrates field survey data collected during three different seasons (spring, summer, and autumn) from both sediment and water samples. The MP concentrations were found to follow an exponential decay pattern from the shore toward the center of the lakes, with higher concentrations near the shoreline. The modeling framework is calibrated using regression analysis, which provides the best-fit parameters for the distance–concentration curves. This study employs sensitivity analysis to justify the decay coefficient, resulting in a selected value of k = 0.09. Model performance is assessed using statistical metrics such as the root mean square error (RMSE) and the coefficient of determination (R²), ensuring accuracy in predicting MP concentrations across different environmental compartments. This work represents a novel contribution to the field by applying numerical modeling techniques to an understudied geographical area. The findings highlight significant seasonal and spatial variations in MP concentrations, emphasizing the need for comprehensive monitoring. This study’s results contribute valuable insights into the environmental behavior of MPs in freshwater systems and support efforts to develop effective management strategies to mitigate pollution. Full article

To investigate the dynamic evolution of macro- and fine-scale characteristics during the compaction process of Stone Mastic Asphalt (SMA-13), the following methodology was employed. First, the compaction characteristics were analyzed based on the Marshall compaction test, and an exponential regression model for compaction was established. A compaction coefficient was proposed to evaluate the ease of compaction of SMA-13. Second, Marshall specimens subjected to different number of blows (5, 15, 25, 50, 75, 100, and 125 times per face) were scanned using a Computed Tomography (CT) scanner, and image processing techniques were applied to precisely extract void characteristics (void number, void area, and equivalent void diameter) under various compaction states. Third, the evolution of void characteristics in SMA-13 during the compaction process was analyzed, and correlations with macroscopic compaction properties were established. The experimental results demonstrated that SMA-13 achieved optimal compaction at an asphalt content of 5.9% and an initial compaction temperature of 170 °C. The established compaction numerical regression model can effectively characterize the compaction characteristics of SMA-13. A higher compaction coefficient indicated easier compaction and better compaction performance. During compaction of SMA-13, the void number and void area exhibited exponential decay, and voids with equivalent diameters of 1–7 mm gradually decreased, showing a non-proportional linear decay in their distribution. In contrast, voids with equivalent diameters of 0–1 mm increased during compaction, and they are the dominant component of the void structure in SMA-13. During compaction, the void ratio of SMA-13 gradually decreased along the direction of height, and the distribution of void ratio was “great at both ends and small in the middle”. The void ratio at 5–55 mm decreased from about 10% to about 0%, and the void ratio distribution was relatively uniform. The void ratio at the bottom 0–5 mm and top > 50 mm was large and unevenly distributed, mostly between 10% and 40%. Full article

Coal seam gas drainage serves as an effective engineering measure to mitigate compound disasters of the rockburst and outburst in deep mining, and its efficacy is fundamentally governed by the permeability of coal around the gas drainage borehole. To systematically study the permeability law of broken coal body around borehole under different stress states and particle size distribution, the coal particle samples were prepared for the triaxial permeability tests by the gradation theory whose Talbot power exponents n are 0.1 to 1.0. Several valuable findings have been obtained through meticulous research and analysis, according to Darcy’s law and the Forchheimer equation. The seepage velocity is affected by the Talbot power exponent, pressure gradient, confining pressure, and axial pressure, among which the pressure gradient has the most prominent influence. The larger the Talbot power exponent of the sample composition and the larger of the pressure gradient inside the sample, the larger is the seepage velocity obtained by the sample. The axial pressure has a notable influence on permeability by modifying the pore structure of broken coal. As the axial pressure increases, the permeability decays exponentially until it reaches a stable state at a specific limit. The permeability decreases exponentially with the increase of effective stress, while the power exponent (a) decreases gradually with the increase of Talbot power exponent, and the coefficient (b) increases gradually with the increase of Talbot power exponent (index), in the effective stress-permeability equation, which implies that the inhibition and amplitude effects of effective stress on permeability become more intense. The permeability shows three stages of growth, namely the slow growth stage, the linear growth stage, and the exponential growth stage, which are influenced by small-sized coal particles, particle-size ratio, and large-sized coal particles respectively, when the Talbot power exponent (n) of the broken coal increases from 0.1 to 1.0. These findings advance understanding of the permeability of broken coal around boreholes, providing theoretical foundations for optimizing gas drainage parameters and preventing the compound disaster of the rockburst and outburst. Full article

This work presents a physics-guided parameter estimation framework for cold spray additive manufacturing (CSAM), focusing on simulating and validating deposit profiles across diverse process conditions. The proposed model employs a two-zone flow representation: quasi-constant velocity near the nozzle exit followed by an exponentially decaying free jet to capture particle acceleration and impact dynamics. The framework employs a comprehensive approach by numerically integrating drag-dominated particle trajectories to predict deposit formation with high accuracy. This physics-based framework incorporates both operational and geometric parameters to ensure robust prediction capabilities. Operational parameters include spray angle, standoff distance, traverse speed, and powder feed rate, while geometric factors encompass nozzle design characteristics such as exit diameter and divergence angle. Validation is performed using 36 experimentally measured profiles of commercially pure titanium powder. The simulator shows excellent agreement with the experimental data, achieving a global root mean square error (RMSE) of 0.048 mm and a coefficient of determination $R^2=0.991$, improving the mean absolute error by more than 40% relative to a neural network-based approach. Sensitivity analyses reveal that nozzle geometry, feed rate, and critical velocity strongly modulate the amplitude and shape of the deposit. Notably, decreasing the nozzle exit diameter or divergence angle significantly increases local deposition rates, while increasing the standoff distance dampens particle velocities, thereby reducing deposit height. Although the partial differential equation (PDE)-based framework entails a moderate increase in computational time—about 50 s per run, roughly 2.5 times longer than simpler empirical models—this remains practical for most process design and optimization tasks. Beyond its accuracy, the PDE-based simulation framework’s principal advantage lies in its minimal reliance on sampling data. It can readily be adapted to new materials or untested process parameters, making it a powerful predictive tool in cold spray process design. This study underscores the simulator’s potential for guiding parameter selection, improving process reliability and offering deeper physical insights into cold spray deposit formation. Full article

In this article, we consider the equations of the nonlinear model of a thermoelastic extensible Timoshenko beam, recently derived by Aouadi in the context of Fourier’s law. The new aspect we propose here is to introduce a second sound model in the temperatures which turns into a Gurtin–Pipkin’s model. Thus, the derived equations are physically more realistic since they overcome the property of infinite propagation speed (Fourier’s law property). They are also characterized by the presence of a symport term. Moreover, it is possible to recover the Fourier, Cattaneo and Coleman–Gurtin laws from the derived system by considering a scaled kernel instead of the original kernel through an appropriate singular limit method. The well-posedness of the derived problem is proved by means of the semigroups theory. Then, we show that the associated linear semigroup (without extensibility and with a constant symport term) is not differentiable by an approach based on the Gearhart–Herbst–Prüss–Huang theorem. The lack of analyticity and impossibility of localization of the solutions in time are immediate consequences. Then, by using a resolvent criterion developed by Borichev and Tomilov, we prove the optimality of the polynomial decay rate of the same associated linear semigroup under a condition on the physical coefficients. In particular, we show that the considered problem is not exponentially stable. Moreover, by following a result according to Arendt–Batty, we show that the linear semigroup is strongly stable. Full article

This study examined the characteristics of rainfall fields in a monsoon climate using seven years of daily rainfall data from 95 stations in eastern China. The stations were located in a region with a flat, low-lying topography, covering approximately 250 km by 150 km. The spatial and temporal properties of the rainfall fields were analyzed from three perspectives: time scales, spatial distance, and direction. Multiple linear regression was applied to explore linear relationships and predict rainfall amounts at selected sites, considering four time scales: 1 day, 3 days, 7 days, and 15 days. The analysis assumed isotropy when examining the distance–decay in the correlation field. The results showed that the distance–decay of the correlation coefficient followed an exponential pattern, with decay rates decreasing as time scales increased. Spatially, north–south variations were more pronounced than east–west variations, and the correlation extended further in latitude than in longitude, highlighting spatial heterogeneity. The correlation coefficient in the wet season was smaller than for the entire year due to dry days and rainfall variability. Additionally, a multi-site linear model was used to interpolate missing rainfall data. The analysis revealed that the goodness of fit improved over longer time scales. Nevertheless, it was also observed that the error ratio simultaneously increased. This implies that when applying distance-weighted interpolation methods, one must exercise due caution. Full article

This study investigates the scattering dynamics of vector Bessel–Gaussian (BG) beams in winter haze environments, with a particular emphasis on the influence of ice-coated haze particles on light propagation. Employing the Generalized Lorenz–Mie Theory (GLMT), we analyze the scattering coefficients of particles transitioning from water to ice coatings under varying atmospheric conditions. Our results demonstrate that the presence of ice coatings significantly alters the scattering and extinction efficiencies of BG beams, revealing distinct differences compared to particles coated with water. Furthermore, the study examines the role of Orbital Angular Momentum (OAM) modes in shaping scattering behavior. We show that higher OAM modes, characterized by broader energy distributions and larger beam spot sizes, induce weaker localized interactions with individual particles, leading to diminished scattering and attenuation. In contrast, lower OAM modes, with energy concentrated in smaller regions, exhibit stronger interactions with particles, thereby enhancing scattering and attenuation. These findings align with the Beer–Lambert law in the single scattering regime, where beam intensity attenuation is influenced by the spatial distribution of radiation, while overall power attenuation follows the standard exponential decay with respect to propagation distance. The transmission attenuation of BG beams through haze-laden atmospheres is further explored, emphasizing the critical roles of particle concentration and humidity. This study provides valuable insights into the interactions between vector BG beams and atmospheric haze, advancing the understanding of optical communication and environmental monitoring in hazy conditions. Full article

Wave attenuation by natural coastal features is recognised as a soft engineering approach to shoreline protection from storm surges and destructive waves. The effectiveness of wave energy dissipation is determined, in part, by vegetation structure, extent, and distribution. Mangroves line ca. 15% of the world’s coastlines, primarily in tropical and subtropical regions but also extending into temperate climates, where mangroves are shorter and multi-stemmed. Using wave loggers deployed across mangrove and non-mangrove shorelines, we studied the wave attenuating capacity and the drag coefficient (C_D) of temperate Avicennia marina mangrove forests of varying structure in Western Port, Australia. The structure of the vegetation obstructing the flow path was represented along each transect in a three-dimensional point cloud derived from overlapping uncrewed aerial vehicle (UAV) images and structure-from-motion (SfM) algorithms. The wave attenuation coefficient (b) calculated from a fitted exponential decay model at the vegetated sites was on average 0.011 m⁻¹ relative to only 0.009 m⁻¹ at the unvegetated site. We calculated a C_D for this forest type that ranged between 2.7 and 4.9, which is within the range of other pencil-rooted species such as Sonneratia sp. but significantly lower than prop-rooted species such as Rhizophora spp. Wave attenuation efficiency significantly decreased with increasing water depth, highlighting the dominance of near-bed friction on attenuation in this forest type. The UAV-derived point cloud did not describe the vegetation (especially near-bed) in sufficient detail to accurately depict the obstacles. We found that a temperate mangrove greenbelt of just 100 m can decrease incoming wave heights by close to 70%, indicating that, similarly to tropical and subtropical forests, temperate mangroves significantly attenuate incoming wave energy under normal sea conditions. Full article

Structural damping is a type of energy dissipation that occurs within the structure of a mechanical system. Unlike other forms of damping that rely on external devices or materials, structural damping is intrinsic to the construction and assembly of the structure itself. This study focuses on the experimental determination of the structural damping ratios for a vehicle front hood fabricated from steel, with the main objective being to accurately identify these damping characteristics. To achieve this, the modal parameter extraction process utilized both the Least Squares Complex Exponential (LSCE) and PolyMAX methods, providing a robust and comprehensive approach to identifying dynamic properties of a hood structure. The hood was subjected to free vibration decay in a free-free condition, with dynamic properties—such as natural frequencies, mode shapes, and damping coefficients—extracted. Additionally, a correlation study was performed between numerical and experimental results, evaluating the Modal Assurance Criterion (MAC) and frequency differences to validate the numerical model’s accuracy. The findings underscore the damping capacity of a standard steel front hood structure and highlight the relationship between damping coefficients and mode shapes, resulting in a well-correlated model for frequency response functions that can be used in transient response calculations. Full article

The limited surface area and structural constraints of small underwater communication devices necessitate a dense placement of transmitting and receiving array elements in optical multiple-input multiple-output (MIMO) systems. The compact layout leads to the formation of sub-channels that exhibit notable spatial correlation and a tendency toward homogeneity. Although sub-channel spatial homogeneity (SSH) may diminish the communication capacity of MIMO systems, it provides a significant advantage by reducing the pilot overhead. In this study, we exploit the inherent SSH and the natural time-domain sparsity of channel impulse response (CIR) in the underwater optical densely arrayed MIMO (UODA-MIMO) system to propose an innovative SSH-based channel estimation (SSH-CE) method. We model the underwater optical CIR at Gbaud rates and integrate it with SSH characteristics. This approach transforms the reconstruction targets of compressive sensing (CS) from conventional CIR samples to prior CIR model parameters and the fitting residuals of the homogeneous sub-channels, reducing the pilot overhead. The simulation results of photon tracing for UODA-MIMO sub-channels in turbid harbor water indicate a monotonic, exponential decay in CIR at Gbaud rates, with transmission delays exceeding 5 nanoseconds for distances over 8 m. Moreover, the correlation coefficients among sub-channels reach a minimum of 0.975, confirming the presence of SSH in UODA-MIMO systems. In comparison to existing CS methods that rely on known sparsity, sparsity adaptation, and the structural sparsity of MIMO channels, the SSH-CE method achieves a lower degree of sparsity in reconstruction targets and a reduced lower bound for pilot requirements under the SPARK criterion. Specifically, the SSH-CE method achieves a reduction in the pilot overhead for reconstructing $N_t$ sub-channels of $\mathcal{K}$-sparse to 2$N_t$ irrespective of CIR residual compensation. Full article