Search Results (4,156)

In this paper, an Artificial Neural Network (ANN) is built to predict the performance of intumescent coatings subjected to the ISO 384 fire curve. The performance metric is called the Retention Loss Onset Time (RLOT) in the structural steel. The network receives the steel and coating thicknesses as input and provides RLOT as the performance of any intumescent coating in a fire accident with substantial accuracy. The required data for obtaining the model is provided by revisiting the recent attempts in this field, which include hybrid numerical and experimental methods. It is found that the trapped gas fraction parameter and empirical expansion ratio substantially affect the accuracy of predictive modelling. Therefore, a new, comprehensive dynamic model that numerically simulates the bubble expansion process has been developed. This novel method directly determines the expansion ratio of the thermal conductivity model. The Eurocode is then used with multi-layer models to predict the steel temperature profile for a 1 h duration ISO fire. The accuracy is improved by modelling the temperatures and thermal resistances at the centre of each divided layer. The effects of different coatings and steel thicknesses are also investigated to provide the required data. The results are verified and validated by comparing them with the recent numerical and empirical results available in the literature. Full article

The dynamic self-assembly and phase separation of donor–acceptor blends are processes that dictate the nanoscale morphology in organic solar cells. Here, we employ a fluidics-inspired framework, integrating dissipative particle dynamics simulations with percolation theory, to investigate the morphogenesis of two non-fullerene systems: P3HT-PPerAcr and P3HT-PFTBT. We analyze monomeric and homopolymer blends, and copolymer macrostructures, focusing on how key parameters such as temperature and polymer chain flexibility govern the dynamic evolution towards percolating networks. Our simulations captured the fundamental fluidic behavior and universal scaling near the critical percolation threshold (χ_c). The critical exponent β revealed distinct universality classes dictated by system compatibility and flexibility: monomeric and flexible homopolymer blends below the critical temperature (T_c) exhibit mean field behavior (β ≈ 1). In contrast, monomeric systems above χ_c and flexible copolymers below χ_c display 3D percolation behavior (β ≈ 0.45). In the case of flexible copolymeric macromolecules, above percolation threshold a quasi-bidimensional behavior emerge with (β ≈ 0.1). Notably, semi-rigid and rigid homopolymeric and copolymeric linear architectures induce a dimensional crossover, yielding quasi-2D (β ≈ 0.14) and quasi-1D (β ≈ 0.0) morphologies. These findings establish a direct link between tunable fluidic interactions, chain dynamics, and the emergence of optimal bicontinuous percolation networks. Full article

In order to reduce the energy consumption of a reverse osmosis seawater desalination system, a study was conducted on the port plate pair that affects the efficiency of the integrated seawater desalination power recovery motor pump. Based on its structural characteristics, a reverse thrust model of the port plate pair was established. A fluid–solid heat multi-field coupling simulation platform was built to study the temperature characteristics of the port plate pair under different conditions. A design method was proposed to use the local temperature characteristics of the port plate pair as the range of residual compression force coefficient values. When the residual compression force coefficient is determined to be 1.05, the compression force of the port plate pair is 33,019 N, the power loss is 307 W, and the temperature reaches 45.1 °C. The simulation accuracy is verified to be 97.31% through experiments. This solved the power loss and local high-temperature problems of the port plate pair and improved the efficiency of the integrated seawater desalination power recovery motor pump. Full article

In this work, a high-performance mid-wave infrared (MWIR) photodetector (PD) utilizing an InAs/GaSb Type-II superlattice absorber and a quaternary AlGaAsSb barrier is designed and analyzed based on numerical simulations aimed at determining an optimized detector structure. Through these simulations, the composition of the AlGaAsSb barrier is carefully designed to achieve lattice matching, high conduction band offset and zero valence band offset. By optimizing the barrier thickness and doping concentration, the depletion region is effectively shifted from the narrow-bandgap absorber to the wide-bandgap barrier; additionally, at 150 K and a reversed bias of 0.05 V, the dark current density in the PD with the barrier (pBn) is reduced to 1.83 × 10⁻⁵ A/cm², about two orders of magnitude lower than that of the PD without the barrier. Furthermore, the effect of the barrier on the generation–recombination (G-R) and the trap-assisted tunneling (TAT) currents are analyzed and compared in detail, and it is found that the barrier structure is much more effective in suppressing the TAT current at low reversed bias when the electric field is low in the absorber layer. These results demonstrate the efficacy of the proposed AlGaAsSb barrier design for realizing high-operating-temperature MWIR PDs. It also provides an insight into the physical mechanism that leads to the performance enhancement of InAs/GaSb PDs. Full article

As urbanization intensifies, improving street thermal comfort has become a critical issue in urban renewal. While existing studies generally assume that increasing the Green View Index (GVI) linearly improves pedestrian thermal comfort, this study identifies a significant “Decoupling Effect” in high-density commercial areas through field measurements and numerical simulations of three typical street types (commercial–service, ecological–recreational, and historical–cultural) in Shenyang. Integrating DeepLab V3 semantic segmentation with ENVI-met version 5.1.1 microclimate simulation, the results demonstrate a robust monotonic negative correlation between GVI and Physiological Equivalent Temperature (PET) in ecological streets (Spearman’s ρ = −0.692, p < 0.001), confirming the consistent cooling benefit of greenery in nature-dominated environments. However, a distinct “Threshold Effect” was identified in commercial streets using Piecewise Linear Regression (PLR). A critical breakpoint was detected at GVI = 22.08%. Below this threshold, visual greenery effectively contributes to cooling (slope = −0.454); yet, once GVI exceeds 22.08%, the cooling efficacy diminishes significantly (slope = −0.109), marking the onset of a “decoupling” phase. Specifically, despite Wenhua Road achieving a GVI of ~24.5% with a complex “three-board, four-belt” structure, its PET peak reaches 46.15 °C, approximately 5.5 °C higher than ecological streets. Mechanism analysis reveals that under peak thermal stress (Traffic Heat ≈ 75 W/m²), the high-intensity anthropogenic heat and hardscape radiation exceed the evaporative cooling threshold of vegetation. This study reveals the non-linear relationship between visual greenery and the physical thermal environment, suggesting that simply pursuing visual green quantity is ineffective in commercial canyon renewal; instead, a threshold-based synergistic optimization of canopy shading and pavement thermal performance is required. These findings provide a quantitative basis for sustainable street landscape planning and urban climate adaptation strategies in high-density cities. Full article

With the shift of oil and gas exploitation to deep seas, the 35 kV high-voltage electric slip ring in Single-Point Mooring (SPM) systems faces critical challenges of insulation failure and thermal failure, threatening operational safety. This study aims to investigate its insulation strength and temperature rise characteristics. A three-dimensional electric field model and a magnetic–thermal coupling model considering the skin effect were established using the finite element method (FEM). Simulations were conducted under four high-voltage configurations and various high-current operating conditions, followed by AC breakdown tests and high-current temperature rise experiments for validation. The results show that the maximum electric field (up to 19.53 kV/mm) concentrates at the inlet polytetrafluoroethylene (PTFE) bushing, which is the insulation weak point. The maximum temperature rise at the center ring can be predicted by a power-law model. Moreover, simulation results agree well with experimental data, confirming the reliability of the computational studies. This work provides a theoretical and experimental basis for the optimal design and safe operation of high-voltage slip rings in offshore SPM systems. Full article

During a tunnel fire, the foremost priority is the safe evacuation of passengers. Extreme temperatures and toxic combustion products can quickly lead to mass casualties, so evacuation support systems require fast forecasts of how hazardous conditions will evolve in space and time. This study investigates whether sparse sensor measurements can be used to reconstruct future tunnel-wide fire conditions on two-dimensional sections that are directly relevant to structural assessment and human exposure. To this end, we develop 2D ST-FAM, a data-driven forecasting model that maps time-resolved measurements from 75 tunnel sensors to future temperature, soot, and carbon monoxide (CO) fields derived from 108 computational fluid dynamics (CFD) fire simulations. The study is organized around three questions: whether the model can accurately reconstruct future tunnel fields from sparse measurements, whether this performance is maintained on both the vertical center plane and the horizontal breathing plane, and which physical quantities remain most challenging to predict. Results show high structural agreement with the CFD reference fields over the full 1800 s prediction horizon, with average structural similarity index (SSIM) values of 0.964 for temperature, 0.984 for CO, and 0.937 for soot. These findings indicate that sparse-sensor forecasting is feasible for tunnel-scale temperature and toxic-gas field prediction, while soot prediction remains comparatively more difficult because of its sharper spatial structures. Full article

Spin-exchange relaxation-free (SERF) atomic magnetometers have emerged as highly promising candidates for ultra-weak magnetic field detection, particularly in biomagnetic imaging, owing to their exceptional sensitivity, amenability to miniaturization, and near-room-temperature operation. While current miniaturized magnetometers typically employ laser chips with fixed optical power, the quantitative impact of laser power on critical performance metrics remains to be fully elucidated. This study systematically investigates the influence of laser power on sensitivity, bandwidth, and dynamic range by incorporating considerations of power broadening, saturation absorption, and noise constraints. A miniaturized probe, integrated with an actively controlled vertical-cavity surface-emitting laser (VCSEL), was developed for experimental validation. Theoretical and experimental results consistently demonstrate that as optical power increases, sensitivity exhibits a non-monotonic dependence, whereas both bandwidth and dynamic range manifest a monotonic upward trend, aligning well with theoretical simulations. The optimized sensor achieved a peak sensitivity of 16 fT/√Hz at 300 μW, while the bandwidth and dynamic range reached 230 Hz and ±5.4 nT at 500 μW, respectively. This work establishes a robust theoretical and experimental framework for the comprehensive performance optimization of laser-integrated miniaturized atomic magnetometers. Full article

Autonomous mobile robots are transforming industries from e-commerce logistics to field exploration, but their effectiveness depends on onboard energy storage. This study addresses the challenge of selecting optimal battery technologies for autonomous mobile robots, balancing performance, energy efficiency, thermal stability, and cost across diverse applications. We focus on lithium-ion, lithium-polymer, and nickel-metal hydride batteries, the most common power solutions, each with distinct advantages and disadvantages in energy density, form factor, thermal stability, and cost. A dynamic modeling and simulation framework in MapleSim evaluated these chemistries under defined and representative operating conditions, tracking state of charge and temperature during charging and discharging. A Particle Swarm Optimization algorithm evaluated 37 battery configurations by thermal stability, energy efficiency, and cost across five use cases. Key results indicate that for logistics and warehousing, lithium nickel manganese cobalt oxide with graphite is optimal; for healthcare, lithium nickel manganese cobalt oxide with lithium titanate oxide excels; for manufacturing, lithium nickel cobalt aluminum oxide with graphite leads; for agricultural robots, lithium manganese oxide with graphite is best; and for exploration and mining, lithium iron phosphate with graphite is most reliable. These results provide a structured basis for battery selection, showing how simulation-driven, multi-criteria decision-making enhances energy management and operational reliability. Full article

Mediterranean tropical-like cyclones (MTLCs), commonly referred to as Medicanes, are high-impact weather systems characterized by complex interactions between baroclinic forcing and tropical-like processes. Despite growing interest, their vertical structures and dynamical regimes remain incompletely understood. In this study, high-resolution Weather Research and Forecasting (WRF) simulations at 1 km resolution are used to investigate the structure and evolution of two dynamically contrasting MTLCs: Ianos (2020) and Qendresa (2014). The analysis focuses on the temporal evolution of kinetic energy and turbulent dissipation as well as on the three-dimensional organization of wind and temperature fields during representative phases of the cyclone life cycle. The results reveal pronounced differences between the two events, with Ianos exhibiting a compact, vertically coherent, convection-dominated structure and Qendresa showing a wider, more asymmetric, and less stationary organization influenced by baroclinic processes. A comparative framework with the ERA5 reanalysis is employed to contextualize cyclone intensity, with ERA5 used as a dynamically consistent large-scale reference rather than as an observational benchmark. Overall, the study highlights the importance of vertical structure and boundary-layer processes in shaping Mediterranean tropical-like cyclones and demonstrates the added value of high-resolution numerical simulations for distinguishing between different dynamical regimes. Full article

Push–pull exhaust systems are widely applied for controlling industry-processing fumes, and their performance is fundamentally governed by the coupling interaction among the air-curtain jet (“push”), the buoyant thermal plume generated by the heat source, and the converging flow induced by the exhaust hood (“pull”). However, the dynamic characteristics and design criteria of this coupled flow field under large temperature differences remain insufficiently explored. Here, a series of scaled experiments combined with numerical simulations is conducted to systematically investigate the coupling behavior of the air-curtain jet and the thermal plume, and two quantitative performance indicators, namely plume deflection height and flow rate along the plume deflection path, are proposed to evaluate flow control effectiveness and energy dissipation. An orthogonal experimental design is further employed to analyze the sensitivity of heat-source and air-curtain parameters with respect to these indicators. The results demonstrate that the air temperature reaches its maximum at approximately 0.8 m downstream of the air-curtain outlet, and that both the supply velocity and outlet width of the air curtain are dominant parameters exerting statistically significant influences on plume deflection height and flow rate along the path (p < 0.01). Furthermore, the Archimedes number effectively characterizes the competition between jet inertia and plume buoyancy in the coupled flow field, with its appropriate value preliminarily recommended to be controlled below 40. This study provides quantitative insights for the engineering design of push–pull exhaust systems operating under high thermal load conditions. Full article

To analyze the fire resistance performance of the substation framework protected by fire-retardant coating, herringbone column structure substation frameworks under heating curve conditions specified by the ISO 834 standard were simulated using ABAQUS software. Moreover, this study investigated the temperature field, stress field, and displacement characteristics of the substation structure under typical fire scene conditions. The research results indicate the following: (1) Without fire-retardant coating, the surface temperature of the bare substation framework reaches 500 °C within a short period, and a large temperature difference between the interior and exterior of the steel pipe is caused, which may induce brittle cracking within the steel. Within the 1000 s period from the start of heating, the strength of the steel structure decreases with the increase in temperature. Stress is gradually concentrated on the steel structure, and the heated part of the bare steel truss undergoes a deformation displacement of more than 0.1 m, making it susceptible to brittle fractures in the steel. The maximum deflection of the steel structures exceeds the critical value of 0.07 m. (2) With fire-retardant coating, the surface temperature of the steel can be maintained below 310 °C, and the stress in most areas of the substation framework remains below 170 Mpa. The displacement and deformation of the transformer frame are significantly reduced, and the deformation can be maintained below 0.02 m. All positions of the substation framework are in the upward expansion stage, and the deflection does not exceed 0.02 m. Full article

During gas production, the wellbore operates under high temperature and high pressure conditions, where gas–liquid two-phase flow is commonly present. Thus, it is important to understand the holdup of different flow patterns of gas–liquid two-phase flow in the wellbore. Currently, prediction models for flow patterns and holdup are mainly based on experimental data obtained under normal temperature and pressure, judged by researchers’ subjective observations, resulting in the lack of a unified flow pattern boundary so far. This article uses CFD simulation to study the characteristics of high temperature and high pressure gas–liquid two-phase flow in wellbores and obtains data such as flow pattern, probability density distribution of gas content, and liquid holdup. The results indicate that pressure is the dominant factor affecting the transition of gas–liquid two-phase flow patterns in wellbores. Under high temperature and pressure, each flow pattern has unique probability density distribution characteristics of gas content, which can be used as a basis for flow pattern identification. Flow pattern diagrams of gas–liquid two-phase flow at room temperature and pressure as well as high temperature and high pressure were drawn, and a boundary model for the transition of gas–liquid two-phase flow patterns in wellbores under the influence of variable pressure was established, verifying the rationality of the flow patterns’ transition boundaries. Based on the simulation of high temperature and high pressure gas–liquid two-phase flow in the wellbore, a calculation model for gas–liquid two-phase flow in the wellbore was established. The absolute percentage error between this model and the Fluent simulation results is within 10%, which can achieve the calculation of gas–liquid two-phase flow in the wellbore under different temperature and pressure conditions. Full article

This study presents a numerical investigation of the effects of atmospheric icing on the aerodynamic performance and power output of the NREL 5 MW reference wind turbine. In cold climate regions, ice accretion on wind turbine blades significantly alters the airfoil geometry, leading to aerodynamic degradation characterized by increased drag, reduced lift, and substantial power losses. Understanding these effects is therefore essential for reliable performance prediction and efficient turbine operation under icing conditions. To address this problem, numerical simulations were conducted on six representative blade sections using the FENSAP-ICE framework, which integrates flow field calculations, droplet transport, and ice accretion modeling within a unified computational environment. The analyses were performed under different atmospheric icing conditions, considering liquid water content values of 0.22 g/m³ and 0.50 g/m³ and ambient temperatures of −2.5 °C and −10 °C. The median volumetric diameter was fixed at 20 µm, and the icing duration was set to one hour for all cases, allowing for both glaze and rime ice formations to be systematically examined. The results reveal that ice accretion becomes increasingly pronounced toward the blade tip, mainly due to higher relative velocities and increased collection efficiency in the outer sections. Glaze icing conditions produce irregular horn-shaped ice formations and lead to severe aerodynamic degradation, whereas rime ice forms more compact structures near the leading edge and results in comparatively lower performance losses. The degraded aerodynamic coefficients obtained from the iced airfoils were subsequently incorporated into BEM-based power calculations, indicating that total power losses can reach up to 40% under severe icing conditions, with the outer blade sections contributing most significantly to this reduction. Furthermore, an economic assessment based on annual energy losses highlights the substantial impact of atmospheric icing on wind turbine performance and operational costs. Full article

Climate change is increasingly affecting groundwater resources in the Carpathian Basin, while rising temperatures are likely to increase irrigation demand and pressure on aquifers. We assessed climate- and pumping-driven impacts on the Nyírség recharge–discharge system (north-eastern Hungary) by combining shallow groundwater monitoring (1970–2022) with hydroclimate indicators from CHIRPS precipitation and ERA5-Land air temperature and snow depth (1981–2024). Using these datasets, we developed and calibrated a MODFLOW groundwater-flow model for representative wet (2010) and dry (2022) conditions, incorporating permitted abstraction and scenario-based estimates of unregistered pumping. We then ran scenario simulations to evaluate mid-century (2050) conditions and managed aquifer recharge (MAR) options. Precipitation exhibits strong interannual variability, but the region shows marked warming and a pronounced decline in snow storage, implying reduced cold-season buffering and higher evaporative demand. Simulations reproduce the observed post-2010 decline in shallow groundwater, with the largest decreases in higher-elevation recharge areas, whereas increased pumping mainly intensifies localized drawdown near major well fields. Scenario results indicate that climate-driven reductions in recharge dominate basin-scale declines by 2050, while MAR provides primarily local benefits; direct subsurface injection performs best among the tested options. These findings support practical groundwater management by prioritizing measurable and enforceable abstraction (including unregistered withdrawals), demand-side irrigation efficiency and adaptive caps in recharge areas, and targeted subsurface MAR where source water and infrastructure are available. Full article