The development of high-efficiency energy dissipation devices is crucial for mitigating the significant threat posed by seismic loads to modern buildings. Therefore, the purpose of this work is to design a novel fluid viscous inerter damper (FVID) and systematically investigate its mechanical performance through theoretical derivations, experiments, and finite element simulations. Furthermore, the impact of FVIDs on the seismic performance of structures is comprehensively evaluated. The advantage of FVID is that under external excitation, the fluid can flow through multiple channels, thereby generating inertial and damping forces to dissipate energy. The theoretical model of FVID’s output force is determined based on FVID’s construction and fluid flow characteristics. The hysteresis performance of the FVID is evaluated through cyclic loading tests, and the influence of the cross-sectional radius and number of turns of the helical tube on its output force is analyzed. By performing finite element simulations of the internal flow field of FVID, the distributions of fluid pressure and velocity at different positions within FVID are analyzed. Based on Simulink, the focus is on investigating the control effect of FVID on structural responses under non-pulse near-field ground motions, pulse-type near-field ground motions, and far-field ground motions. The results indicate that the FVID has a strong energy-dissipation capacity and can effectively reduce structural responses under different types of earthquakes. The cross-sectional radius of the helical tube is a key design parameter that determines the damper’s output force. For highly destructive pulse-type near-field ground motions, FVIDs still exhibit excellent comprehensive performance in the structure.

In 2025, escalating consumption of fossil fuels has driven the atmospheric CO2 concentration to 430 ppm, which is the highest value in human history. Photoelectrocatalytic CO2 reduction offers a viable strategy to mitigate CO2 levels, while addressing the surging demand for fossil energy. Herein, an in situ synthesis strategy of a solvothermal method combining with successive ionic layer adsorption and reaction (SILAR) was developed to fabricate a 3D honeycomb-structured In2S3/CdS heterojunction on carbon paper mimicking plant cells for PEC CO2 reduction. The carbon paper substrate exhibits an excellent photothermal effect, with its surface temperature reaching 65 °C. Photochemical and photoelectrochemical analyses indicate that the formation of the heterojunction can effectively enhance the utilization of photogenerated carriers. Thus, the optimal In2S3/CdS-4h catalyst reduces CO2 to HCOOH, CH3COOH, and CH3CH2OH products under mild reaction conditions, with a carbon-based product formation rate of 28.75 μM h-1 cm-2 and an electron selectivity for C2 products of 88.8%. Repeated experiments reveal a favorable reproducibility of In2S3/CdS-4h photoelectrodes with the RSD lower than 10%. Moreover, the In2S3/CdS-4h heterojunction exhibits improved stability, retaining 70.5% of its initial activity after five cycles (10 h), whereas CdS retains only 53.8%. Considering the underlying mechanism, optical simulations and chemical field simulations confirm the benefits of this honeycomb structure on light absorption and C2 product selectivity, respectively. Operando IR spectra identified the key *OCHO and *OC-COH intermediates responsible for the formation of the C1 and C2 products, respectively. Finally, DFT calculations show that the In2S3/CdS interface specifically promotes C-C coupling (forming *OC-COH) compared with the individual components. This work presents a perspective for the rational design of catalysts via multieffect synergy, advancing efficient PEC CO2 reduction to C2 products.

Study on the recrystallization of 0Cr17 ferritic stainless steel under multiple factors: A 3D phase field simulation

A physically constrained hybrid modeling framework for real-time simulation of parabolic trough solar field in CSP plants

Impact of tube configuration on UV-C sterilization efficacy in continuous-flow milk treatment: Numerical simulation of flow field, inactivation kinetics and energy consumption analysis

This study investigates the flow field and aerodynamic characteristics of a two-dimensional trajectory correction projectile equipped with an actively controllable air-ducts structure suitable for spin-stabilized projectiles, using both numerical simulation and wind tunnel testing. The flow field structural characteristics of the projectile are analyzed under varying Mach numbers and angles of attack, and the effects of internal air duct geometric parameters on aerodynamic performance are examined. Wind tunnel experiments further validate the projectile’s radial correction capability under low-speed flight conditions. Key findings indicate that the lateral air jet generated by the oncoming airflow is smoothly discharged in both subsonic and supersonic regimes, and interactions between the lateral jet and oncoming flow at the duct outlet propagate downstream, altering the mid-to-rear flow field structure. The internal duct diameter directly affects aerodynamic forces: a 72% increase in diameter produces a 234.2% rise in lateral force under identical conditions. The outlet duct angle relative to the projectile axis strongly influences flight stability: a 13% increase in outlet duct angle θ reduces lateral force by 19% while increasing pitch moment by 15.1% and yawing moment by 37.5%. Minor axial displacements of the lateral outlet relative to the center of mass have negligible effects on overall aerodynamic performance. Experimental results confirm that the air-ducts structure provides measurable radial correction capability, demonstrating the effectiveness of the proposed aerodynamic modification scheme.

Numerical simulation of temperature field in photovoltaic glass calendering process

Improved methods for assessing summer thermal environments in tropical urban beaches: Combining field measurements and simulation

The assessment of flood defense structures is essential for community resilience and disaster prevention. Within these structures, the potential for erosion and piping mechanisms poses critical risks, often leading to severe infrastructure damage. Breach initiation and growth are the main causes of dam and levee failure, which is directly affected by the phreatic line. This study introduces a natural element method (NEM) formulation with Sibson interpolation specifically tailored to directly estimate the phreatic line in homogeneous earthen embankments, avoiding conventional mesh generation and reducing preprocessing effort. The main innovation is the combination of a mesh-free NEM scheme with an iterative free-surface update dedicated to phreatic line tracking, rather than full embankment flow field simulation. Comparative analyses and validation against existing data emphasize the method’s strength. Validation against piezometric data from a railway embankment in Cumbria (UK) and the IJkdijk full-scale test levee (Netherlands) shows average relative errors below 2% and maximum errors under 10%, demonstrating that the proposed NEM approach can reproduce observed phreatic levels with high accuracy using relatively few nodes. These results indicate that the method provides an accurate and practically attractive tool for phreatic line assessment in flood defense structures, suitable for integration into levee and embankment safety evaluations.

Abstract Electric field simulations based on individualized Magnetic Resonance Imaging (MRI)-derived head models are increasingly used to optimize non-invasive brain stimulation (NIBS) protocols, enabling individualized dose adjustments to achieve a desired current flow at cortical targets. However, the quality of structural MRI data—affected by motion artefacts, tissue contrast, and scanner-related noise—may influence the accuracy of these simulations, an issue possibly exacerbated in older adults who often exhibit lower image quality. If reduced image quality compromises electric field estimation, it could limit the feasibility of individualized dosing in aging populations. In this study, we examined whether standardized image quality metrics—entropy focus criterion (EFC), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), spatial resolution (FWHM), and intensity non-uniformity (INU)—systematically relate to the magnitude of simulated electric fields in young and older adults. We analysed MRI and simulation data of a focal C3 montage from 106 healthy adults, 47 young adults (mean age: 24.8, age range: 20–35 years) and 59 older adults (mean age: 69.5 years, age range: 60–79) using SimNIBS for computational modelling of the electric fields and MRIQC for image quality assessment. Structural equation modelling was used to quantify direct and indirect effects of age group on electric field magnitude, with image quality as a mediating factor. Head volume was included in extended models to control for anatomical variation. Our findings demonstrate that MR image quality is associated with simulated electric field magnitude, with higher EFC, lower SNR, lower CNR, and higher INU associated with reduced field estimates, and older adults showing generally lower simulated electric fields compared to younger adults. While image quality accounted for some of the age-related differences in electric field strength, group differences remained even after controlling for EFC, SNR and head volume. Critically, electric field simulations remained sufficiently reliable despite lower image quality in older adults, supporting their use for individualized dose adjustment across the lifespan.

Ceramic capacitors, although promising for advanced high-power energy storage, face challenges in energy density and efficiency at high temperatures, which restricts their practical applications. Guided by phase field simulations, we propose a structural design strategy to construct weakly coupled polar nanoclusters in superparaelectric state, and fabricate BaTiO3-based multilayer ceramic capacitors via prototype device technology. The capacitors achieve an ultrahigh energy storage density of 19.0 J·cm-3 and a high energy storage efficiency of 95.5% at room temperature. More importantly, both metrics are still on the order of > 10.0 J·cm-3 and > 95.0%, respectively, over 25-160 oC, outperforming previously reported ceramic capacitors. The weaken coupling between adjacent nanoclusters caused by disordered polar configurations, suppresses nonlinear polarization response and temperature sensitivity, ultimately enabling superior energy storage performance, which is confirmed by atomic-scale microstructure analysis. This work advances next-generation electronics and provides insights for developing high-performance high-temperature ceramic capacitors.

Objective. Tumor treating fields (TTFields) is an emerging cancer therapy whose efficacy is closely linked to the electric field (EF) intensity delivered to the tumor. However, current computational workflows for simulating the EF and planning treatment rely on time-consuming manual segmentation and proprietary software, hindering efficiency, reproducibility, and accessibility.Approach. We introduce AutoSimTTF, a fully automatic pipeline for personalized EF simulation and optimized treatment planning for TTFields. The end-to-end workflow utilizes advanced deep learning model for automated tumor segmentation, conducts finite element method-based EF simulation, and determines a computationally optimized treatment plan via a novel, physics-based parameter optimization method.Main results. The automated segmentation module achieved high precision, yielding a Dice similarity coefficient of 0.91 for the whole tumor. In terms of efficiency, the active planning workflow was completed in approximately 12 min, significantly outperforming conventional multi-day manual processes. The pipeline's simulation accuracy was validated against a conventional semi-automated workflow, demonstrating deviations of less than 14.1% for most tissues. Critically, the parameter optimization generated personalized transducer montages that produced a significantly higher EF intensity at the tumor site (up to 111.9% higher) and substantially improved field focality (19.4% improvement) compared to traditional fixed-array configurations.Significance. AutoSimTTF addresses major challenges in efficiency and reproducibility, paving the way for data-driven personalized TTFields therapy and large-scale computational research.

Numerical simulation is widely employed to analyze optical transmission performance in flow fields. However, time-continuous flow fields produce large data volumes, and dynamic aero-optical analysis requires substantial computational resources, resulting in low efficiency with the conventional method. Consequently, this study proposes the data-driven adaptive micro element reconstruction (DAMER) method. DAMER significantly improves computational efficiency in aero-optical simulations of time-continuous flow fields through eliminating redundant data, reducing computational load and interpolation requirements, and enabling continuous, precise adaptive step-size adjustment. In addition, unlike conventional approaches that empirically determine step-size ranges, DAMER introduces a method for defining step-size ranges across diverse computational fluid dynamics (CFD) grid scales. Simultaneously, DAMER simplifies the identification of intersections between rays and irregular optical windows in 3D flow fields. In the cases evaluated, DAMER achieved speedups of 131.10 and 11.56 compared to the conventional method for 2D and 3D continuous flow fields, respectively. These advancements improve aero-optical analysis by significantly enhancing computational efficiency and accuracy.

Magnetohydrodynamic (MHD) acceleration is considered to have great potential to extend the operational range of supersonic ground test facilities. However, this technique has not been fully utilized due to the lack of understanding of its mechanism. Clarification is urgently needed in the dependency relationship of vital parameters on MHD acceleration such as magnetic field and plasma conductivity. This study makes such an endeavor by simulating the process of MHD acceleration using a three-dimensional MHD acceleration channel model. Parameter scanning simulations of magnetic field and conductivity are conducted separately to examine their impact on supersonic MHD acceleration. Results show that the performance of MHD acceleration is improved with the increase in magnetic field, but only within a limited range. Suppression of current density in higher magnetic field hampers the velocity increase. The positive role of a higher magnetic field is counteracted by the reduction in current density at higher magnetic fields, indicating counteractive relation leading to an optimal equilibrium for maximum acceleration performance. Conductivity scanning simulations show that the outlet velocity ratio increases almost linearly with conductivity elevation. Joule heating power also rises with higher conductivity, but does not generate a negative pressure gradient which is supposed to slow the flow. Aerodynamic effect may play a role in the process in cooling down the flow and lowering the pressure, suggesting that controlling conductivity may be more effective to enhance MHD acceleration performance.

ABSTRACT Structural mechanics field simulation plays a critical role in the vibration characteristic analysis of electrical equipment. Existing structural field analysis of equipment based on numerical simulation faces challenges such as convergence difficulties and prolonged computational time, failing to meet the demand for real‐time prediction of equipment status. In the rapid structural mechanics analysis of dry‐type iron core reactor, the sparsity of snapshot matrix will compromise the computational efficiency of proper orthogonal decomposition (POD) algorithm and introduce substantial approximation errors in reduced‐order models (ROMs). An improved POD method based on stochastic gradient descent (SGD) is proposed to realise the fast decomposition and calculation of sparse snapshot matrix in the paper. First, the SGD method is applied to the optimisation of snapshot matrix constructed from structural field simulation. Then, POD method is employed to extract the dominant reduced‐order modes and the corresponding modal coefficient. Finally, a graph neural networks‐based surrogate model is constructed to realise the rapid prediction of reactor vibration. Compared with conventional model reduction methods, the proposed method significantly improves the efficiency in handling rapid vibration simulation of dry‐type iron core reactor, and the calculation error also decreases by 14.1%.

Wurtzite III-nitride compounds are CMOS-compatible with widespread industrial interest to exercise ferroelectricity, despite their polar structure being highly resistant to polarization reversal. Here, we induce and tune ferroelectric properties in w-AlN via direct-write ion-beam processing, using nanoscale patterned defect engineering as a post-growth alternative to conventional cation substitution. Nanometric piezoresponse spectroscopy of the focused He+ beam patterned defect concentrations in ferroelectric Al0.92B0.08N measures a localized 10x enhancement in effective piezoresponse and 40% reduction in switching barrier. The irradiation-induced point defects convert piezoelectric AlN into a ferroelectric system with site-saturated nucleation and raise the dielectric susceptibility, switched polarization, and effective piezoelectric coefficient. Enhanced defect-lattice interactions in AlN increase carrier conduction and phonon scattering loss but preserve long-range crystallinity. Based on atomistic analysis of nudged elastic band density functional theory calculations and reactive force field simulations, both nitrogen vacancies and defect complexes disrupt bond ordering, facilitating a line-by-line low-barrier switching of pristine AlN.

Abstract In this study, the influence of the hydrodynamic damping models on the floater dynamics of a semi-submersible floating offshore wind turbine (FOWT) was investigated both numerically and experimentally. Semi-submersible FOWT substructures typically consist of pontoons and vertical columns. These submerged components exhibit dynamic behavior under the combined influence of waves and currents. The drag force induced by the structure's shape and the damping force caused by fluid viscosity interact in a complex manner, influencing the floater's dynamic motion. During the early design stage, the platform's response characteristics are typically evaluated through integrated load analysis. To better approximate the dynamic behavior observed in the actual structure, it is important to construct a suitable damping model that can represent the real damping characteristics of the system. In this study, a damping model was constructed by integrating results from CFD simulations and 1/36-scale model experiments. The linear and quadratic damping coefficients were determined through the results of free decay experiments conducted in still water. The nonlinear Morison drag coefficient was obtained from a uniform flow field simulation using CFD. The characteristics of three models—linear damping, linear-plus-quadratic damping, and Morison drag—were compared, and a method for combining them was proposed. The validity of the combined damping model was confirmed by applying it to the floating substructure.

This study investigates the electric field distribution and breakdown characteristics of oil-paper insulation in a 500 kV converter transformer under AC/DC superimposed voltages. The electric field distribution within the winding end insulation structure at the valve side was analyzed under various voltage conditions using finite element simulations. Experiments were conducted on insulating oil and oil-paper samples to measure their breakdown strengths under different AC/DC components. The results reveal that under DC voltage, the electric field concentrates inside the insulation paper, whereas under AC voltage, it is mainly distributed across the oil gap. Under AC/DC superimposed voltages, a decreasing AC ratio shifts the electric field from the oil gap to the insulation paper and increases the maximum electric field strength. As the DC component rises, the breakdown strength of both oil and oil-paper samples first decreases and then increases, with oil-paper insulation consistently exhibiting higher strength. These findings indicate that although oil-paper insulation can withstand higher electric fields and thus ensure transformer safety, low DC components may increase the risk of oil discharge or failure. Therefore, the design of next-generation high-voltage converter transformers must account for oil-paper insulation degradation under low DC ratios, and effective mitigation strategies—such as controlling the internal electric field or enhancing dielectric strength—are essential for ensuring reliability under AC/DC superimposed voltages.

ABSTRACT Oblique incidence ultrasonic backscattering is an important method for characterising the internal microstructure of polycrystalline materials. However, in existing measurements, the coupling effects between oblique incidence angles and cylindrical bars significantly compromise the inversion accuracy. To address this issue, this paper proposes a three-dimensional multi-parameter correction (3D-MPC) method based on single scattering response theory. The ultrasonic field in the transducer’s single scattering response model was decomposed into three dimensions to establish the 3D-MPC model. Subsequently, numerical simulations were performed to analyse the variation of the correction parameters with the incident angle. On this basis, three-dimensional acoustic field simulations were conducted to further illustrate, through representative examples, that the correction model improves the single scattering response model by optimising the single Gaussian beam under oblique incidence. In addition, a series of controlled-variable experiments were conducted on the induction-hardened 40Cr bar, with EBSD measurements along the radial depth serving as the reference data. Compared to the results without correction, the introduction of the 3D-MPC model significantly improved the inversion accuracy of the grain size-depth distribution. The average absolute improvement in accuracy across the six experimental datasets was approximately 12% (ranging from 5.72% to 15.75%), demonstrating the overall effectiveness and reliability of the proposed correction method.

Accurate simulations of electric fields (E-fields) in neural stimulation depend on tissue conductivity representations that link underlying microscopic tissue structure with macroscopic assumptions. Mesoscale conductivity variations can produce meaningful changes in E-fields and neural activation thresholds but remain largely absent from standard macroscopic models. Conductivity variations within the cortex are expected given the differences in cell density and volume fraction across layers. We review recent efforts modeling microscopic and mesoscopic E-fields and outline approaches that bridge micro- and macroscales to derive consistent mesoscale conductivity distributions. Using simplified microscopic models, effective tissue conductivity was estimated as a function of volume fraction of extracellular space, and the conductivities of different cortical layers were interpolated based on experimental volume fraction. The effective tissue conductivities were monotonically decreasing convex functions of the cell volume fraction. With decreasing cell volume fraction, the conductivity of cortical layers increased with depth from layer 2 to 6. Although the variation of conductivity within the cortex was small when compared to the conductivity of extracellular fluid (9% to 15%), the conductivity difference was considerably larger when compared between layers, e.g., with layer 3 and 6 being 20% and 50% more conductive than layer 2, respectively. The review and analysis provide a foundation for accurate multiscale models of E-fields and neural stimulation. Using layer-specific conductivity values within the cortex could improve the accuracy of estimations of thresholds and distributions of neural activation in E-field models of brain stimulation.