Search Results (73)

This study analyzes the combined effects of non-Newtonian rheology and electrostatics on the transient electroosmotic flow of Maxwell fluids in soft channels. The walls of the rigid channels are hydrophobic, ionically charged, and coated with a polyelectrolyte layer (PEL). This design is intended to regulate both the surface electric potential and the flow velocity. The mathematical model is based on modified Poisson–Boltzmann and momentum equations, which are solved numerically using a one-dimensional (1D) approach. The results indicate that high potentials, exceeding the Debye–Hückel limit, are achieved under conditions of thick polyelectrolyte layers, high surface charge density, and a higher concentration of fixed charges compared to the electrolyte ionic concentration. In this regime, steric effects increase the electric potential; however, this potential increase is limited by the formation of a Donnan potential. The hydrodynamic analysis demonstrates that the velocity magnitude is influenced not only by the wall potential but also by the spatial distribution of free charge density and electroosmotic force, which, in turn, are affected by steric effects. Additionally, changing the polarity and concentration of fixed charge in the PEL produces asymmetric flows, and while hydrodynamic slip enhances velocity, the drag parameter reduces it. Finally, the dimensionless parameters that control the time required to dampen the oscillatory flow induced by viscoelastic effects and reach steady-state are mainly the relaxation time, the drag parameter, the PEL thickness, and the electrokinetic parameter of the PEL, while the surface charge density and the external pressure gradient exert a comparatively minor influence. Full article

Low-temperature photoluminescence (PL) has been studied under hydrostatic pressure and varying excitation powers in three samples of single In_0.17Ga_0.83N quantum wells with different widths: 2.6 nm, 5.2 nm, and 10.4 nm. Transitions involving ground states were strong in the 2.6 nm well, weak in the 5.2 nm well, and absent in the 10.4 nm well. Pressure coefficients of PL lines have been used to estimate the electric field in the wells. In the widest well, the field seems to be fully screened (at high excitation powers). Simulations involving Poisson and Schrödinger equations allowed us to identify the experimental PL lines. Pressure evolution of the PL spectra agreed with the simulation. We present diagrams showing the dependence of the field in the well on pressure and on carrier concentration. In wide wells, these diagrams illustrate the transition from a 2D-like system to a 3D-like system. Full article

This study investigates the pressure-dependent structural, electronic, mechanical, and thermoelectric properties of LiYN (Y = Sr, Mg, Zn) half-Heusler compounds using first-principles calculations. The structural stability was analyzed by fitting the total energy versus volume curves using the Birch–Murnaghan equation of state, allowing the determination of equilibrium lattice parameters and bulk moduli at pressures of 0, 5, and 10 GPa. Elastic constants were calculated to assess the mechanical stability, and all compounds satisfy the Born stability criteria over the entire pressure range. The Pugh ratio (B/G) and Poisson’s ratio (ν) indicate that LiSrN, LiMgN, and LiZnN exhibit predominantly brittle behavior under 0 GPa. Electronic band structure calculations reveal that LiMgN and LiZnN exhibit direct band gaps, whereas LiSrN shows an indirect band gap. Increasing pressure leads to a systematic widening of the band gaps due to lattice compression. Thermoelectric properties were evaluated using the Boltzmann transport theory within the constant relaxation time approximation. The Seebeck coefficient, electrical conductivity, and figure of merit (ZT) were found to be strongly dependent on both temperature and pressure. Notably, at 300 K, the ZT values increase from 0.005, 0.35, and 0.54 at 0 GPa to 0.027, 1.12, and 1.13 at 10 GPa for LiMgN, LiSrN, and LiZnN, respectively. These results demonstrate that hydrostatic pressure significantly enhances the thermoelectric performance of LiYN compounds, highlighting their promising potential for thermoelectric energy conversion applications. Full article

Background/Objectives: Cystatin C-based and combined creatinine–cystatin C estimated glomerular filtration rate (eGFR) equations improve early chronic kidney disease (CKD) detection and prediction of adverse outcomes compared to creatinine alone. However, their role in predicting microvascular complications such as diabetic retinopathy (DR) is less clear. We examined the association between diabetic kidney disease (DKD), defined using creatinine-, cystatin C-, and combined eGFR measures, as well as albuminuria, and the risk of incident DR among Asian adults in Singapore. Methods: We analysed 1135 Chinese and Indian adults with diabetes aged ≥40 years from a population-based cohort study with baseline (2007–2011) and 6-year follow-up (2013–2017) data. DR was graded from retinal photographs, and incident DR was defined as new-onset at follow-up. DKD was defined as eGFR < 60 mL/min/1.73 m² using eGFRcr, eGFRcys, combined eGFRcr-cys, and albuminuria (UACR ≥ 30 mg/g), assessed individually and jointly. Modified Poisson regression models adjusted for age, sex, ethnicity, diabetes duration, HbA1c, and systolic blood pressure were used to estimate relative risks (RRs). Results: Overall, incident DR occurred in 13.0% of participants. Among those with DKD, incidence was 18.2% (eGFRcr), 16.7% (eGFRcys), 23.7% (eGFRcr-cys), and 18.3% (albuminuria). eGFRcr-DKD (RR = 2.18, 95% CI 1.33–3.58), eGFRcys-DKD (2.38 [1.51–3.78]), and eGFRcr-cys-DKD (3.15 [1.94–5.12]) were independently associated with incident DR, whereas albuminuria alone was not. Risk increased with increasing number of markers,2.00 (1.02–3.92) by dual and 4.91 (2.50–9.65) by triple markers. Conclusions: DKD defined using multiple kidney markers, particularly combined creatinine–cystatin C, was strongly associated with incident DR. These findings support the use of multiple kidney function markers to improve risk stratification for developing DR. Full article

This work numerically reveals a novel strategy to modulate two ionic conductance state in a nanochannel via pressure-dependent fluidic motion inside the channel. Steady and transient simulations based on Poisson–Nernst–Planck–Stokes equations demonstrate that the two states with distinct ionic conductance and ion selectivity can be reversibly switched by external pressure, with a characteristic time of ~100 μs. Furthermore, the two conductance states are found to depend on the transversal electric field, which gives rise to two distinct intrachannel fluidic flow patterns, namely laminar flow and vortex flow, respectively. This finding suggests the potential of pressure-controlled ionic conductance switching for applications in nanofluidic ionic circuits, flow-regulated sensing, and integrated micro/nanoscale devices. It also provides insights into nonlinear ionic current–voltage behaviors. Full article

In this study, density functional theory (DFT) within the generalized gradient approximation (GGA) is employed to investigate the structural, electronic, mechanical, and thermoelectric properties of perovskite hydrides XZrH₃ (X = Mg, Ca, Sr, Ba). Mechanical stability and ductility are evaluated through the Cauchy pressure, Pugh’s ratio, and Poisson’s ratio, all of which point to ductile behavior with a dominant ionic-bonding character. Electronic structure calculations reveal metallic behavior arising from band overlap at the Fermi level. Equilibrium energy–volume data are fitted with the Murnaghan equation of state, and transport coefficients are extracted using the BoltzTraP package as implemented in WIEN2k. The absence of a band gap and the overlap between valence and conduction bands confirm conductor-like behavior. Lattice thermal conductivity for MgZrH₃, CaZrH₃, SrZrH₃, and BaZrH₃ increases monotonically with temperature. Overall, the results identify MgZrH₃ in particular as a promising candidate for thermoelectric devices and solid-state hydrogen storage, thereby supporting progress toward a sustainable hydrogen economy. Full article

The compression deformation of seed cotton has been identified as a key factor affecting the working reliability of the baling device and the quality of bale molding. However, due to the complex working conditions of seed cotton in the continuous compression process in a confined space, it has proven to be difficult to study the compression molding mechanism of machine-harvested seed cotton in the baling process. The present study employs a universal testing machine to compress the seed cotton. In addition, pressure sensors are utilised to ascertain the internal axial load transfer law of the seed cotton. Furthermore, the internal density distribution equation of the seed cotton is established. Moreover, the Fiber model is employed to establish a spatial helix structure model of the cotton fibre. Finally, the compression simulation test is conducted to calibrate its material parameters. The results of the study indicate that seed cotton exhibits hysteresis in its internal stress–strain transfer. Through the polynomial fitting of the compression–displacement curve, it has been demonstrated that as the seed cotton approaches the compressed side, the rate of change in compression increases. The internal density distribution of the seed cotton must be calculated when it is compressed to a density of 220 kg·m⁻³. It is found that the density of the upper layer of the seed cotton is slightly greater than that of the lower layer of the seed cotton. The density distribution equation must then be obtained through regression fitting. The parameters of the compression model must be calibrated by means of uniaxial compression tests. Finally, the density distribution equation of the cotton fibre must be obtained through the compression test. The parameters of the simulation model, as determined by the uniaxial compression test calibration, are of significant importance. This is particularly evident in the context of the Poisson’s ratio of cotton fibre and the cotton fibre elastic modulus under pressure. The regression equation was obtained through analysis of variance, and the simulation of contact parameter optimisation. The optimal parameter combination was determined to be 0.466, and the pressure at this time. The relative error was found to be 2.96%, and the compression of specific performance was determined to be 10.14%. These findings serve to validate the simulation model. The findings of this study have the potential to provide a theoretical foundation and simulation assistance for the design and optimisation of cotton picker baling devices. Full article

Particle image velocimetry (PIV) flow measurements are common practice in laboratory settings in a wide variety of fields involving fluid dynamics, including biology, physics, engineering, and medicine. Dynamic fluid pressure is a notoriously difficult property to measure non-intrusively, yet its variation is a driving flow force and critical to model correctly. Techniques have been developed to estimate the pressure from velocity and velocity gradient measurements. Here, we highlight a novel application of boundary conditions when applying such pressure estimation techniques based on two-dimensional PIV data; the novel method is especially relevant to problems with complex boundary conditions. As such, it is demonstrated with PIV measurements of in vivo fish suction-feeding, which represents a challenging flow environment. Suction-feeding is a common method for capturing prey by aquatic organisms. Suction-feeding is a complex fish–fluid interaction governed by various hydrodynamic forces and the dynamic behavior of the fish (motion and forces). This study focuses on estimating the pressure within the flow field surrounding the mouth of a Bluegill sunfish (Lepomis macrochirus) during suction-feeding utilizing two-dimensional PIV measurements. High-speed imaging was used for measurements of the fish kinematics (duration and amplitude). Through the Poisson equation, the pressure field is estimated from the PIV velocity measurements. The boundary conditions for the pressure field are determined from the integral momentum equation, separately for three phases of the suction-feeding cycle. We demonstrate the utility of the technique with this case study on fish suction-feeding by quantifying the pressure field that drives the flow towards the buccal cavity, a feeding mechanism known to be dominated by pressure spatial variations over the feeding cycle. Full article

This article presents a comparison of empirical and simulation studies and the parameters declared by the membrane manufacturer. The analysis concludes that these values differ at each stage. Therefore, a numerical and simulation analysis of an optimal flat membrane was undertaken, which will successfully perform measurement functions across the full pressure range without causing inelastic deformations based on a membrane made of 316 L stainless steel with the following mechanical parameters: Young’s modulus $\mathrm{E}=2\times {10}^{11} \mathrm{P}\mathrm{a}$, Poisson’s ratio $\mathsf{\nu }=0.28$, density $\mathsf{\rho }=7980 \mathrm{k}\mathrm{g}/{\mathrm{m}}^3$, and yield strength 2.8 × 10⁸ Pa. A diaphragm with an outer diameter of 25.4 mm, an inner diameter of $2.22\times {10}^{-4} \mathrm{m}$, and a thickness of t = $5.08\times {10}^{-5} \mathrm{m}$ was designed for a pressure sensor in vacuum extinguishing chambers of medium-voltage devices, with a pressure difference $\Delta \mathrm{p}$ from 7 × 10⁻⁴ Pa to 1.013 × 10⁵ Pa. Finite element method (FEM) simulations in the COMSOL Multiphysics environment showed maximum von Mises reduced stresses 1.96 × 10⁸ Pa below the yield strength, confirming operation in the linear-elastic range. The central deflection, described analytically by the equation $\mathrm{y}={\displaystyle \frac{3(1-{\mathsf{\nu }}^2)\mathrm{P}{\mathrm{r}}^4}{16\mathrm{E}{\mathrm{t}}^3}}$, increased fivefold with an increase in diameter to $3.81\times {10}^{-2} \mathrm{m}$ (active area A = 1.14 × 10⁻³ m² compared to 5.07 × 10⁻⁴ m²), achieving a metrological sensitivity of 9.1 × 10⁻¹⁰ m/Pa. Experimental studies integrated with Bragg FBG and epoxy adhesive (E = 5 × 10⁹ Pa, tensile strength $4.2\times {10}^7 \mathrm{P}\mathrm{a}$) revealed a significant deviation from the manufacturer’s catalog data (e.g., deflection of $2.0\times {10}^{-5} \mathrm{m}$ at $6.89\times {10}^2 \mathrm{P}\mathrm{a}$), resulting from uneven bonding and a lack of coaxiality. Corrugated membranes with t = $2.0\times {10}^{-5} \mathrm{m}$ exceeded plasticity, while the optimized configuration of a smooth membrane with rounded adhesive edges ($\mathrm{R}=1\times {10}^{-4} \mathrm{m}$) enabled precise pressure monitoring below ${10}^{-1} \mathrm{P}\mathrm{a}$, despite technological restrictions on assembly and miniaturization. Full article

Background: Almaty, located in a mountain–valley basin, frequently experiences stagnant conditions that trap pollutants and cause sharp diurnal contrasts in air quality. Current forecasting systems either offer detailed physical realism at high computational cost or yield statistically accurate but physically inconsistent results. Urban air quality in mountain–valley cities is strongly shaped by thermal inversions and weak nocturnal ventilation that trap pollutants close to the surface. We present a hybrid physics–machine-learning framework that combines a Navier–Stokes surface-layer model with data-driven post-processing to produce short-term forecasts of wind, temperature, and particulate matter while preserving physical consistency. The approach captures diurnal ventilation patterns and the well-known negative linkage between near-surface wind and particulate loadings during wintertime inversions. Compared with purely statistical baselines, the hybrid system improves short-range forecast skill and maintains interpretability through physically grounded diagnostics. Beyond Almaty, the workflow is transferable to other mountain–valley environments and is directly actionable for early warning, traffic and heating-related emission management, and health-risk communication. By uniting physically meaningful fields with lightweight Machine Learning correction, the method offers a practical bridge between computational fluid dynamics and operational decision support for cities facing recurrent stagnation episodes. Aim: Develop and verify a method for the diagnostics and short-term forecasting of surface circulation and particle concentrations in Almaty (2024), ensuring physical consistency of fields, increased forecast accuracy on 6–24 h horizons, and interpretability of risk factors. Compared to purely statistical baselines (R² ≈ 0.55 for PM forecasts), our hybrid framework achieved a 16% gain in explained variance and reduced RMSE by 25%. This improvement was most evident during winter inversion episodes. Methods: This study introduces a hybrid modeling framework that integrates the Navier–Stokes equations with machine-learning algorithms to diagnose and forecast surface air circulation and particulate matter concentrations. The approach ensures both physical consistency and improved predictive accuracy for short-term horizons (6–24 h). The Navier–Stokes equations in the Boussinesq approximation, the energy equation, and K-closure particulate matter transport were used. The numerical solution is based on the projection method (convection—TVD/QUICK, pressure—Poisson equation). The ML module is gradient boosting and decision trees for meteorological parameters, lags, and diagnostic quantities. The 2024 data are cleaned, normalized, and visualized. Results: The hybrid model reproduces the diurnal cycle of ventilation and concentrations, especially during winter inversions. For 6 h: wind RMSE ≈ 1.2 m/s (R² ≈ 0.71), temperature RMSE ≈ 1.8 °C (R² ≈ 0.78), and particles RMSE ≈ 0.012 mg/m³ (R² ≈ 0.64). Errors are higher for 24 h. A negative relationship between wind and concentration was established: +1 m/s reduces the median by 10–15% during winter nights. Conclusions: The approach can be generalized to other mountain–valley cities beyond Almaty. Combining the physical model and ML correction improves short-term predictive ability and maintains physical consistency. The method is applicable for air quality risk assessment and decision support; further clarification of emissions and consideration of urban canyon geometry are required. The results support early-warning systems, health risk communication, and urban planning. Full article

We investigate the geometric and physical properties of the h-almost conformal $\eta$-Ricci–Bourguignon soliton and its gradient form by employing a barotropic equation of state within the framework of $f(\mathcal{R},\mathcal{T})$ gravity. We derive this barotropic equation of state under the assumption that the matter content of $f(\mathcal{R},\mathcal{T})$ gravity is modeled by a barotropic perfect fluid. We also examine the way in which these soliton structures both reveal and limit the underlying symmetries of the spacetime geometry. Furthermore, we obtain modified Poisson and Liouville equations associated with these solitons in such a gravitational setting. Additionally, we explore certain harmonic aspects of the h-almost conformal $\eta$-Ricci–Bourguignon soliton on a spacetime filled with a barotropic perfect fluid, considering a harmonic potential function $\mathrm{\Psi }$. Finally, we present physical interpretations of the conformal pressure $\tilde{p}$ in the context of the h-almost conformal $\eta$-Ricci–Bourguignon soliton within $f(\mathcal{R},\mathcal{T})$ gravity. Full article

This study addresses computational challenges in the immersed boundary method (IBM) with the pressure implicit with split operator (PISO) algorithm for simulating incompressible flows. We introduce a novel time-step splitting method to implement communication overlapping optimization, aiming to reduce costs dominated by the pressure Poisson solver. Using a fast Fourier transform (FFT)-based approach, the Poisson equation is solved efficiently with $O(NlogN)$ complexity. Our method interleaves IBM force calculations with Poisson phases, employing asynchronous communication to overlap computation with global data exchanges. This reduces communication overhead, enhancing scalability. Validation through benchmark simulations, including flow around a cylinder and particle-laden flows, shows improved efficiency and accuracy comparable with traditional methods. Implemented in a custom C++ solver using the FFTW library, tests indicate substantial acceleration, with results showing a 40% speed-up and less than 3% deviation in drag and lift coefficients. This research provides an efficient and promising simulation tool for complex flow. Full article

The implementation of lean drilling and completion design techniques is a pivotal strategy for the petroleum and natural gas industry to achieve green, low-carbon, and intelligent transformation and innovation. These techniques significantly enhance oil and gas recovery rates. In shale gas development, the shale brittleness index plays a crucial role in evaluating fracturing ability during hydraulic fracturing. Indoor experiments on Gulong shale oil were conducted under a confining pressure of 30 MPa. Based on Rickman’s brittleness evaluation method, this study performed numerical simulations of triaxial compression tests on shale using the finite discrete element method. The fractal dimensions of the fractures formed during shale fragmentation were calculated using the box-counting method. Utilizing the obtained data, a multiple linear regression equation was established with elastic modulus and Poisson’s ratio as the primary variables, and the coefficients were normalized to propose a new brittleness evaluation method. The research findings indicate that the finite discrete element method can effectively simulate the rock fragmentation process, and the established multiple linear regression equation demonstrates high reliability. The weights reassigned for brittleness evaluation based on Rickman’s method are as follows: the coefficient for elastic modulus is 0.43, and the coefficient for Poisson’s ratio is 0.57. Furthermore, the new brittleness evaluation method exhibits a stronger correlation with the brittleness mineral index. The fractal characteristics of crack networks and the relationship between symmetry response and mechanical parameters offer a new theoretical foundation for brittle weight distribution. Additionally, the scale symmetry characteristics inherent in fractal dimensions can serve as a significant indicator for assessing complex crack morphology. Full article

The structure and memory organization of graphics processor units (GPUs) manufactured by NVIDIA and the use of CUDA programming technology to solve computational fluid dynamics (CFD) problems is reviewed and discussed. The potential of using a general-purpose GPU to solve fluid dynamics problems is examined. The code optimization with the utilization of various memory types is considered. Some CFD benchmark problems focused on simulation of viscous incompressible fluid flows are solved on GPUs. Consideration is given to the application of the finite volume method and projection method. Programming implementation of various components of the computational procedure, solution of Poisson equation for pressure and multigrid method to solve the system of algebraic equations, is provided. By using meshes of varying resolutions and different techniques for dividing up the input data into blocks, the speedup of the GPU solution is compared to the CPU approach. Full article

Compressional (V_P) and shear (V_S) wave velocities of polycrystalline vanadium were measured simultaneously up to 11.5 GPa at room temperature using ultrasonic interferometry in a multi-anvil press. Complex softening behavior in V_S and resulting shear moduli are discovered, possibly revealing a precursor to the reported phase transition within 30–60 GPa. The current data enables a comprehensive assessment of the elastic and mechanical properties of vanadium at high pressures, including bulk and shear moduli, Young’s modulus, Poisson’s ratio, and Pugh’s ratio. Through fitting to the 3rd-order finite strain equations, the elastic moduli and their pressure derivatives were determined to be K_S0 = 151 (2) GPa, G₀ = 46.9 (8) GPa, K’_S0 = 3.47 (5), and G’₀ = 0.62 (1). These experimental results allow us to compare with and benchmark the existing Steinberg–Guinan models for extrapolations to extreme pressure and temperature conditions. Full article