Search Results (4,064)

The simultaneous analysis of geometric morphology and thermodynamic states from heterogeneous sensing modalities is essential for high-temperature industrial inspection. While supervoxel segmentation is effective for extracting fine structures, conventional fixed-weighting schemes often struggle with the inherent heterogeneity between spatial sensors and thermal sensors. This paper proposes a segmentation framework for thermo-geometric point clouds based on Pareto-optimal weight learning and gradient anisotropy. A multi-objective evolutionary optimization algorithm is employed for multi-modal Pareto weight learning to adaptively balance geometric and thermal constraints. The developed gradient-anisotropic supervoxel generation algorithm introduces a local saliency factor to achieve fine-grained thermodynamic segmentation. Furthermore, a gradient damping mechanism is implemented to ensure high thermal-boundary adherence even in geometrically planar regions by imposing anisotropic penalty forces. Finally, a region-growing method based on the optimized multi-sensor fusion weights is utilized to merge similar supervoxels. Experimental results demonstrate that our approach outperforms traditional baselines by achieving high-fidelity thermal segmentation and multi-modal boundary preservation, while accepting a modest and necessary compromise in geometric compactness to accommodate spatial–thermal inconsistencies. Full article

Traditional topology optimization methods often face challenges such as slow convergence, high sensitivity to initial structures, and limited exploration of the design space when dealing with multi-physics coupling problems. To address these challenges, this study proposes an efficient design framework integrating reinforcement learning and topology optimization. The framework first employs a Deep Q-Network (DQN) agent to dynamically adjust penalty factors, accelerating the convergence process, and uses its pre-optimization results as the initial conditions for the Bidirectional Evolutionary Structural Optimization (BESO) method, thereby enhancing optimization efficiency and structural performance. By introducing an anisotropic material model, the design space is expanded, further unlocking the potential for structural lightweighting. On this basis, a dual-objective optimization strategy for mechanical compliance and thermal compliance is adopted, enabling the final structure to adapt to various physical working conditions. Finally, the optimal design is extended from two-dimensional to three-dimensional, facilitating subsequent manufacturing and verification. Numerical examples demonstrate that compared with traditional methods, the proposed pre-optimization method achieves a 22.463% reduction in structural compliance and improves thermal management performance. The framework demonstrates robust convergence across different boundary conditions (MBB and cantilever beams) and expands the design space through anisotropic microstructures, offering a practical solution for multi-physics lightweight design. Full article

Triaxial induction logging is particularly outstanding in identifying reservoir parameters including anisotropic strata, inclined boreholes and horizontal wells. However, the coplanar systems follow the traditional induction method of using a shielding coil to offset the direct coupling. This method results in severe horns in the coplanar coil response, which makes it more difficult to evaluate the water (oil) saturation of the reservoir. In this study, we used an analytic method to derive the magnetic field in a finite-thickness anisotropic medium by applying tangential continuity of the electric and magnetic field strengths, introducing the magnetic vector potential and Bessel functions. The response model influenced by different parameters was established. Under the same environmental parameters, the measurement range of the vertical and horizontal conductivities was larger than that of the traditional coplanar system. The apparent conductivity of the target layer was closer to the true value of the vertical conductivity in the layered strata, with an accuracy improvement of 78.9%. Furthermore, the improved coplanar system mechanism was revealed by analyzing the spatial distributions of eddy currents and the magnitudes of the magnetic fields generated. Finally, we designed an experimental device for a coplanar sensing system. Under the same parameters, the received signals of the improved coplanar system were greater than those of the traditional coplanar system in the air, which laid a foundation for the quantitative evaluation of stratigraphic anisotropy response characterization and inversion. Full article

Permeability anisotropy, which is widely present in natural soil deposits, plays an important role in controlling groundwater flow patterns and ground deformation during deep excavation dewatering. However, isotropic assumptions are still commonly adopted in engineering practice, making it difficult to accurately capture realistic subsurface hydraulic conditions. In this study, a deep foundation pit of a metro station in Jinan, China, is taken as a case study. A three-dimensional excavation–dewatering model incorporating permeability anisotropy is established using PLAXIS 3D to systematically investigate the influence of the permeability ratio (Kx/Kz) ranging from 0.1 to 10 on the seepage field evolution, dewatering influence radius, ground surface settlement, and consolidation time history. The results indicate that increasing permeability anisotropy promotes a fundamental transition of the seepage regime from vertically concentrated recharge to laterally dominated radial flow. Correspondingly, the dewatering influence radius exhibits a pronounced non-monotonic response to Kx/Kz, decreasing significantly with increasing permeability ratio and reaching a minimum at approximately Kx/Kz ≈ 5, followed by a slight rebound. Meanwhile, surface settlement profiles evolve from a localized concentration pattern to a widely distributed form as permeability anisotropy increases, accompanied by a remarkable outward expansion of the settlement influence zone. Both the magnitude and spatial distribution of settlement show high sensitivity to variations in permeability anisotropy. Based on these findings, a three-stage conceptual seepage structure model accounting for permeability anisotropy is proposed, characterized by vertically dominated flow, a transitional competition regime, and horizontally dominated flow. The staged evolution of seepage structures is shown to govern the non-monotonic variation in the dewatering influence radius and the spatial–temporal response of ground settlement. The results indicate a dual-scale influence mechanism of permeability anisotropy on dewatering-induced hydro-mechanical behavior, providing a theoretical basis for refined dewatering design and environmental impact assessment in deep excavation projects. Full article

Cancer remains a primary global health challenge, accounting for millions of new cases and significant mortality annually. Although doxorubicin (DOX) is a fundamental anthracycline used for various malignancies, its therapeutic index is severely limited by poor selectivity, systemic toxicity, and dose-dependent cardiotoxicity. To address these issues, Janus nanoparticles (JNPs) have emerged as a promising bifunctional platform characterized by a structural asymmetry that allows for the independent functionalization of each hemisphere. This review examines primary fabrication routes—such as masking, microfluidics, self-assembly, and phase separation—and their specific applications in DOX delivery. The anisotropic architecture of JNPs enables a “separate rooms” concept, allowing for the co-delivery of incompatible drugs while facilitating multi-stimuli-responsive release mechanisms triggered by pH, enzymes, or NIR light. Furthermore, JNPs have demonstrated enhanced tumor accumulation and reduced systemic toxicity compared to conventional isotropic carriers. Recent developments even highlight the use of autonomous nanomotors to improve therapeutic delivery while minimizing premature leakage. However, clinical translation is currently hindered by manufacturing complexity, high equipment costs, scalability issues, and a lack of standardized reporting in the literature. Ultimately, JNPs represent a sophisticated frontier in precision oncology, though robust manufacturing processes and characterization protocols are required for future medical adoption. Full article

Silicon carbide (SiC) has emerged as a highly attractive material for microelectromechanical systems (MEMS) operating in harsh environments, owing to its outstanding mechanical, thermal, and chemical properties. This review provides a comprehensive overview of the advantages and limitations of SiC-based MEMS, with particular emphasis on the strong interdependence between material structure, mechanical properties, and epitaxial growth processes. The role of defects, residual stress, and crystal quality is discussed in relation to device performance and reliability. Special attention is devoted to cubic SiC grown on silicon substrates, highlighting how growth-induced features influence the mechanical response of micromachined structures. Furthermore, a detailed analysis of the quality factor (Q-factor) is presented for 3C-SiC (111)/Si resonators, including the development of analytical models and their validation through numerical simulations performed using COMSOL Multiphysics (Version 6.1). The necessity of incorporating anisotropic loss factors in numerical modeling is demonstrated to be essential for accurately describing the experimentally observed behavior. This review aims to provide design guidelines and modeling strategies for the optimization of SiC MEMS, supporting their further development for high-performance and extreme-environment applications, including pressure sensors, mechanical resonators and high-stress-tolerant sensors. Full article

This paper presents a collaborative optimization design methodology aimed at improving heat dissipation efficiency through the modulation of microstructural variations. The approach addresses the thermal protection requirements of high-temperature components, such as ceramic matrix composite turbine blades, which are subjected to complex and elevated thermal loads. Through the integration of numerical simulation and experimental validation, a bidirectional mapping model linking carbon nanotube (CNT) content with the macroscopic anisotropic thermal conductivity of the material was developed. Furthermore, a thermal conduction analysis and optimization framework for Ceramic Matrix Composite (CMC) high-temperature components under non-uniform thermal loads was established. This study expands the adjustable range of the material’s thermal conductivity by allowing flexible modulation of carbon nanotube content. The results demonstrate that this methodology effectively enhances the heat dissipation capacity of CMC materials in extreme thermal environments: the maximum surface temperature of the optimized flat plate is reduced by 8.96%, the peak temperature gradient is lowered by 46.64%, and the maximum thermal stress is decreased by 38.17%. This research provides new insights into the comprehensive integration of thermal dissipation requirements for CMC hot components. Full article

Driven by the demand for miniaturization, high capacitance, and enhanced reliability in high-performance multilayer ceramic capacitors (MLCCs), the continuous thinning of inner electrode layers imposes increasingly stringent requirements on the size, distribution, morphology, and dispersion of nano-nickel powders. We systematically investigate how functional additives regulate the nucleation, growth, and microstructural evolution of nano-nickel synthesized via hydrazine-driven liquid-phase reduction of nickel sulfate. The results demonstrate that the alkanolamine complexing agent (TAC) significantly refines the average particle size and morphology of the nano-nickel through coordination effects. Furthermore, inorganic sulfur salts (ISP), acting via surface adsorption to passivate growth sites and provide catalytic effects, enable a precise and continuous reduction in the average particle diameter from 330 nm down to 60 nm at a mere trace dosage of ~10⁻⁷ mol/L. Regarding dispersion optimization, highly dispersed face-centered cubic (FCC) nano-nickel was successfully prepared by introducing multidentate carboxylate (NNA). High-resolution transmission electron microscopy (HRTEM) was employed to unveil, for the first time, the crystallographic origin of the anomalous surface protrusions typically observed in conventional reaction systems. We confirmed that the family of $\left\{10\overline{1}0\right\}$ crystal planes within these regions, which exhibits interfacial angles of 58.7° and 58.3°, corresponds to a thermodynamically metastable hexagonal close-packed (HCP) nickel phase originating from atomic stacking faults induced by rapid growth kinetics. To address this microstructural defect, a thioether-based amino acid (TAA) was introduced. TAA effectively suppresses the anisotropic growth of the metastable HCP phase through the strong steric hindrance of its long side chains and its selective adsorption onto high-energy facets. Full article

In-pipe robots must navigate narrow, curved passages where rigid mechanisms often require bulky steering units. Soft crawlers offer better compliance but typically rely on multiple actuators or reconfigurable contacts to achieve multi-directional motion. Drawing inspiration from biological soft crawlers that exploit directional friction and coordinated anchor–slip patterns, this study focuses on locomotion principles observed in caterpillars, water boatmen, and whirligig beetles. Based on these bioinspired concepts, we present a tendon-driven soft in-pipe robot that combines continuum bending–twisting deformation with modular anisotropic friction pads (AFPs), enabling three locomotion modes using only two motors. AFP inclination, curvature, and ridge geometry were optimized through friction tests, constant-curvature modeling, and finite element analysis to enhance directional adhesion on flat and curved surfaces. A deformation-based locomotion framework was developed to couple tendon actuation with friction orientation, achieving longitudinal crawling, transverse translation, in-place rotation, and smooth transitions via programmed twisting. Driving experiments demonstrated repeatable anchor–slip locomotion with average speeds of 28.6 mm/s, 15.7 mm/s, and 11.5°/s for the three modes. Pipe tests in straight, curved, and T-junction sections further validated stable contact and reliable gait transitions. These findings highlight the potential of friction-programmed continuum robots as compact, bioinspired platforms for advanced in-pipe inspection and diagnostic tasks. Full article

Rubber–textile conveyor belts with polyester–polyamide (EP) carcasses are widely used in bulk material handling, where their mechanical performance significantly affects their reliability, safety and service life. Due to the anisotropic structure of the textile reinforcement, the deformation of EP belts is strongly dependent on the loading direction. This study investigates the deformation rate behavior of rubber–textile conveyor belts under uniaxial tensile loading, with an emphasis on the differences between the longitudinal (warp) and transverse (weft) directions. The experimental results show that the strain rate is controlled by different deformation mechanisms of the textile components, which leads to significantly different deformation kinetics under warp and weft loading. The findings provide new insights into the time-dependent tensile behavior of EP belts and support the optimization of the textile carcass design for better durability and sustainability under severe operating conditions. Full article

Lanthanum silicate oxyapatite (LSO) is a promising oxide ion conductor for low-temperature-operating electrochemical devices owing to its high ionic conductivity along the c-axis. However, the fabrication of thin films with controlled crystallographic orientation remains challenging. In this study, polymer-assisted deposition (PAD), a solution-based technique offering precise microstructural and compositional control, was employed to fabricate c-axis-oriented LSO thin films. The fabrication of undoped LSO and the effects of Al and Mg incorporation on its microstructure, orientation, and ionic conductivity were systematically investigated. Undoped LSO thin films crystallised with a preferential c-axis orientation in the annealing temperature range of 800 and 1100 °C, and scanning transmission electron microscopy observations revealed a highly crystalline, void-free microstructure. Upon annealing at 1200 °C, the undoped LSO exhibited columnar grains with anisotropic in-plane grain growth, whereas Al- or Mg-doped LSO suppressed anisotropic in-plane grain growth and retained an out-of-plane c-axis orientation. The undoped LSO showed higher in-plane ionic conductivity than the doped thin films, consistent with their distinct crystallographic orientations. These results demonstrate that PAD provides a viable pathway for tailoring the microstructure and the composition of LSO thin films, thereby facilitating their applications in solid oxide electrochemical devices. Full article

In this paper, we present a multi-parallel restricted additive Schwarz (MP-RAS) preconditioner construction method for cardiac electrophysiology simulation. This method is designed to address the need for solving large-scale linear systems in realistic cardiac electrophysiology simulations and can provide a more efficient computational tool for patient-specific electrical propagation modeling, arrhythmia studies, and the evaluation of ablation strategies. The proposed preconditioner is suitable for the finite element simulation of the anisotropic cardiac monodomain model. In particular, we construct the subdomains based on Morton code sorting, build submatrices by indices and decompose the formula for parallel computing. Given that the computing of each subdomain is relatively independent, the iteration can be extended to N-parallel. Numerical experiments indicate that for matrices of the same size and under the same number of partitions, Morton code sorting is at least 105 times faster than METIS, while the memory usages are reduced by 12∼32%. The iteration number is reduced by approximately two times compared with the Jacobi and block Jacobi preconditioned conjugate gradient (PCG) method. Comparative experiments with other solvers further demonstrate that the MP-RAS solver is highly efficient for solving this parabolic partial differential equation and have strong parallel scalability. Full article

Monitoring of blade vibrations in turbomachinery equipped with ferromagnetic blades is currently performed using the Blade Tip-Timing (BTT) non-contact technique. To reduce measurement uncertainty on time samples, BTT systems require measurement probes to meet high dynamic performance requirements. Anisotropic magnetoresistive (AMR) sensors have recently gained interest for this application owing to their high sensitivity to magnetic flux variations and robustness in harsh, contaminated environments. However, a thorough dynamic characterization of AMR-based BTT probes remains largely unexplored, representing a critical gap in next-generation industrial measurement systems. This work presents a custom-designed signal conditioning circuit tailored for AMR-based BTT measurements, alongside a systematic methodology for characterizing its dynamic performance. The circuit is modeled as a block diagram, from which transfer functions are derived analytically and validated experimentally, providing a rigorous and reproducible framework for probe dynamic assessment. The complete instrumentation chain is then tested on a low-speed rotor test bench in a BTT configuration. Results reveal a fundamental sensitivity–bandwidth trade-off: satisfying the cutoff frequency requirement imposed by BTT applications inherently reduces signal gain below the threshold needed to resolve individual blade-passage events. This finding isolates the key design bottleneck for AMR-based BTT probes and provides quantitative guidance for future optimization of both sensor and circuit design toward industrial tip-timing deployment. Full article

Mechanical confinement plays an important role in regulating tumor growth and invasion; however, the quantitative, time-resolved, three-dimensional evaluation of confined tumor spheroids remains technically challenging. In this study, we developed a custom-built selective plane illumination microscopy (SPIM)-based monitoring platform for long-term volumetric imaging of tumor spheroids under mechanically confined conditions. This system integrates a culture housing unit and a transparent cuvette-based spheroid culture method optimized for SPIM observation. Colorectal adenocarcinoma-derived cell spheroids were embedded in agarose gels with defined concentrations to modulate the stiffness of the surrounding matrix. Bright-field imaging and viability analyses confirmed sustained spheroid growth without necrotic core formation over a 4-day culture period, demonstrating that the SPIM-based system maintained the physiological culture conditions. Three-dimensional imaging using SPIM enabled a quantitative evaluation of spheroid growth and anisotropic invasion. Volumetric expansion was observed under all confinement conditions. Notably, increasing the matrix stiffness enhanced both the volumetric growth rate and anisotropic invasion, indicating stiffness-dependent directional growth under mechanical confinement. The developed SPIM-based platform has the potential to serve as a practical tool for the time-resolved three-dimensional analysis of tumor spheroid growth and may provide a useful approach for investigating the mechanobiological regulation of tumor progression in confined microenvironments. Full article

This article comprehensively reviews the fatigue crack growth (FCG) models applied to Ti6Al4V alloy manufactured by electron beam melting (EBM) powder bed fusion (PBF). The current progress in FCG analytical and numerical models and their application to EBM Ti6Al4V are reviewed. Much experimental data for the creation of historical FCG models was based on conventionally manufactured (CM) aluminum alloys and various steels. With the growth of additive manufacturing (AM), recent studies have applied traditional models and modified new models to EBM Ti6Al4V and validated their use as accurate predictive models for the da/dN-ΔK curve and ΔK_th. Due to pores and surface roughness inherent in AM and the unique anisotropic microstructure developed from the EBM process, classical models may require modifications to accurately predict FCG of EBM Ti6Al4V. Full article