Search Results (621)

Three-dimensional printing (3DP) has gained increasing attention in construction as a means of addressing labor shortages and improving efficiency. Various studies have investigated fiber-reinforced mortars for 3DP. However, only a few studies have examined mixture design strategies aimed at controlling early structural build-up, and the relationships between early structural build-up, printability, and interlayer stability remain largely unexplored. This study aimed to establish a practical method for evaluating the static yield stress and early buildability of 3DP mortars under construction-site conditions. Vane shear and 15-stroke flow tests were conducted to assess the static and dynamic behavior of mortars incorporating polyvinyl alcohol (PVA) fibers, and their compressive and flexural strengths were also evaluated. According to the results, the vane shear test sensitively captured the rheological changes associated with variations in fiber content and superplasticizer dosage. The addition of PVA fibers increased the maximum shear stress of the mortar, resulting in atypical static yield stress development compared to fiber-free mortars. While the 15-stroke flow test further elucidated flowability, the vane shear test revealed a stronger correlation between mechanical properties and overall buildability. Thus, vane shear testing can be reliably used to assess early-age structural build-up and interlayer stability in 3DP mortars for optimizing print performance. Full article

The hyperloop transportation system is a promising ultra-high-speed mobility solution operating in a reduced-pressure environment, where pod performance is governed by the coupled behaviour of structural integrity, aerodynamics, and electromagnetic propulsion. This paper presents the design, numerical analysis, and performance evaluation of a lightweight hyperloop pod equipped with a linear induction motor (LIM)-based propulsion and electromagnetic stabilisation system. The pod chassis was fabricated using Carbon Fibre-Reinforced Polymer (CFRP) and Aluminium 6061-T6, achieving a significant weight reduction while maintaining structural safety. Finite Element Analysis reveals a maximum von Mises stress of 82 MPa, which is well below the material yield strength, and a maximum deformation of 0.64 mm under worst-case loading conditions. Modal analysis indicates the first natural frequency at 47.6 Hz, ensuring sufficient separation from operational excitation frequencies. Computational Fluid Dynamics analysis conducted inside a rectangular tube shows a drag coefficient reduction of approximately 18% compared to a baseline blunt design, with stable velocity distribution and no flow choking at operating speeds. The optimised nose geometry enables rapid acceleration, achieving 25 km/h within 1.1 s in prototype testing. The LIM analysis demonstrates a peak thrust of 1.85 kN at an optimal slip range of 6–8%, with operating currents between 35 and 55A and power consumption of 18–25 kW. Thermal analysis confirms a maximum stator temperature of 78 °C, remaining within safe operating limits. The integrated numerical and experimental results confirm the feasibility, efficiency, and stability of the proposed hyperloop pod design. Full article

The growing demand for direct reduced iron (DRI) in green steel production requires high-quality fired pellets as the burden for the gas-based shaft furnace direct reduction process. However, the properties of magnetite concentrate as pellet feed present a significant impact on the quality of fired pellets, especially the metallurgical performance. A systematic study of the effect of pretreating the magnetite concentrate on the properties of fired pellets was conducted using two pretreatment technologies, i.e., damp-milling and high-pressure roll grinding (HPRG). Green balls were made from pretreated magnetite concentrates and fired under optimal conditions. Their performance was then evaluated in a laboratory-scale setup simulating the HYL shaft furnace environment. Key metrics included cold compressive strength (CCS), reducibility index (RI), reduction swelling index (RSI), and dynamic low-temperature reduction degradation (LTD). The pretreatment of magnetite concentrates with HPRG twice showed significant benefits. The fired pellets not only have a CCS of 2500 N/p at a roasting temperature 150 °C lower, but also achieve an RI of 3.37 and an RSI of 3.15%, respectively. Furthermore, the reduction degradation tendency was markedly reduced; the +6.3 mm fraction reached 94.72% with a whole pellet ratio of 75.49%. Conversely, while damp-milling improved the LTD, it required a 100 °C increase in preheating temperature and yielded a whole pellet ratio of only 49.15%, failing to meet industrial requirements. The improvement in metallurgical performance is attributed to the intense micro-cracking induced by the two-pass HPRG process, which optimizes the particle size distribution, specific surface areas and improves the microstructure and pore properties of the fired pellets. Full article

Theoretical studies of transonic accretion onto black holes reveal a wide range of possible solutions, broadly classified into smooth flows and flows featuring shocks. Accretion solutions that involve the formation of shocks are particularly intriguing, as they are expected to naturally produce observable variability features. However, despite their theoretical significance, time-dependent studies exploring the stability and evolution of such shocked solutions remain relatively scarce. To address this gap, we perform simulations of transonic accretion flows around a black hole in an ideal magnetohydrodynamic framework. Our simulations are initialized using boundary conditions derived from semi-analytical hydrodynamical models, allowing us to explore the stability of these flows under varying magnetic field strengths. Our results indicate that mildly magnetized flows in a uniform vertical magnetic field alter the accretion dynamics through magnetic pressure, with the resulting force imbalance driving oscillations in the shock front. Variations in the emitted luminosity arising from shock oscillations appear as quasi-periodic oscillations (QPOs), a characteristic feature commonly observed in accreting black holes. We find that the QPO frequency is determined by the radial position of the shock front: oscillations occurring closer to the black hole produce frequencies of tens of hertz, whereas shocks located farther out yield sub-hertz frequencies. Full article

The mechanical behavior of metallic core–shell nanoparticles is critical for their use as reinforcement particles and additive manufacturing feedstocks, yet their deformation mechanisms remain incompletely understood. This study employs molecular dynamics simulations to investigate the compressive response of a Cu-core/Al-shell nanoparticle and compares it with solid Cu, solid Al, and a hollow Al shell of the same size under uniaxial loading along ⟨100⟩, ⟨110⟩, ⟨111⟩, and ⟨112⟩ directions. The single-material nanoparticles show strong anisotropy: solid Cu exhibits orientation-dependent transitions from dislocation slip to deformation twinning, while introducing a void to form a hollow Al shell reduces stiffness and strength, confines plasticity to the shell wall, and suppresses extended load-bearing twins. The Cu–Al core–shell nanoparticle combines these behaviors in an orientation-dependent manner. Under ⟨110⟩ and ⟨112⟩ loading, deformation is largely shell-dominated, whereas ⟨100⟩ and ⟨111⟩ loading more strongly activates the Cu core. Mechanistically, ⟨100⟩ is characterized by Shockley partial activity and junction/lock formation in the Al shell coupled with twinning in the Cu core; ⟨110⟩ shows primarily shell partials with limited core involvement; ⟨111⟩ promotes partial-dislocation activity in both shell and core; and ⟨112⟩ produces localized, twin-dominated bands in the Al shell with shell-thickness-dependent twin extension into the Cu core. These trends are rationalized using Schmid factor considerations for $\left\{111\right\}⟨110⟩$ slip and $\left\{111\right\}⟨112⟩$ partial/twinning shear, together with the effects of faceted free surfaces and the Cu–Al interface. The core–shell geometry enables two concurrent interface-mediated pathways, i.e., (i) stress transfer and reduced cross-interface transmission and (ii) circumferential bypass within the shell, which together yield only slight flow-stress increases over solid Al while markedly reducing stress serrations compared with both solid Cu and solid Al. Across all orientations, the core–shell structures also exhibit delayed yielding (higher yield strain) relative to solid Cu, indicating enhanced ductility. The results provide an atomistic basis for designing Cu–Al core–shell nanoparticles for robust particle-based processing and additive manufacturing feedstock, and for informing multiscale models with mechanism-resolved, orientation-dependent inputs. Full article

Background: Bucket-wheel excavators are critical assets in surface mining operations, where structural modifications to increase productivity must be validated through rigorous stress analysis to ensure operational safety. Following modification of an ERc 1400-30/7 excavator’s bucket wheel from 18 to 20 buckets, increased operational loads necessitated experimental verification of structural integrity. Methods: A custom 10-channel strain-gauge data acquisition system with 0–10 kHz bandwidth measured stresses in cable anchoring lugs and H-type diagonal members under operational conditions at the Jilț lignite mine, Romania. Measurements were performed during both left and right bucket-wheel rotation. Finite element analysis validated experimental results. Results: Maximum equivalent stresses of 210.0 MPa and 167.1 MPa were measured in the left and right anchoring lugs, respectively, during left bucket-wheel rotation, representing 59% and 47% of material yield strength with safety factors of 1.69 and 2.12. Significant load asymmetry was observed, with left rotation inducing 220–284% higher stresses than right rotation. FEA validation showed <15% agreement with measurements. Dynamic stress amplification of 15–32% above quasi-static values was attributed to bucket–soil interaction and structural vibration. Conclusions: Despite increased operational loads, measured stresses remain below yield strength, confirming structural adequacy. Both anchoring lugs require prioritized monitoring due to elevated stress levels and load asymmetry. The validated methodology provides a framework for post-modification verification of large mining equipment. Full article

This article presents a novel framework for encrypting color images to enhance digital data security using deep learning and artificial intelligence techniques. The system employs a two-model neural architecture: the first, a Convolutional Neural Network (CNN), verifies sender authenticity during user authentication, while the second extracts unique fingerprint features. These features are converted into high-entropy encryption keys using Particle Swarm Optimization (PSO), minimizing key similarity and ensuring that no key is reused or transmitted. Keys are generated in real time simultaneously at both the sender and receiver ends, preventing interception or leakage and providing maximum confidentiality. Encrypted images are secured using the Advanced Encryption Standard (AES-256) with keys uniquely bound to each user’s biometric identity, ensuring personalized privacy. Evaluation using security and encryption metrics yielded strong results: entropy of 7.9991, correlation coefficient below 0.00001, NPCR of 99.66%, UACI of 33.9069%, and key space of 2²⁵⁶. Although the final encryption employs an AES-256 key (key space of 2²⁵⁶), this key is derived from a much larger deep-key space of 2⁸¹⁹² generated by multi-layer neural feature extraction and optimized via PSO, thereby significantly enhancing the overall cryptographic strength. The system also demonstrated robustness against common attacks, including noise and cropping, while maintaining recoverable original content. Furthermore, the neural models achieved classification accuracy exceeding 99.83% with an error rate below 0.05%, confirming the framework’s reliability and practical applicability. This approach provides a secure, dynamic, and efficient image encryption paradigm, combining biometric authentication and AI-based feature extraction for advanced cybersecurity applications. Full article

Adiabatic shear banding (ASB) is a critical failure mechanism in titanium alloys subjected to high-strain-rate deformation, and its initiation is strongly influenced by the initial crystallographic texture. The dynamic response and ASB sensitivity of extruded and annealed Ti-6Al-4V (TC4) alloy rods were investigated under dynamic compression of cubic specimens along the extrusion direction (ED) and the transverse direction (TD) at a strain rate of 2500 s⁻¹. Split Hopkinson pressure bar (SHPB) tests combined with digital image correlation (DIC) were employed to obtain the stress–strain response and the evolution of strain localization. A dislocation density-based crystal plasticity finite element model (CPFEM), incorporating the measured texture, was established to elucidate the correlation between texture and ASB behavior. The experimental results show that TD specimens exhibit a yield strength approximately 100 MPa higher than that of ED specimens, while both orientations display comparable post-yield hardening behavior. ASB initiation occurs earlier in TD (compressive strain ~0.13) than in ED (~0.23), indicating greater ASB sensitivity in the TD orientation. The CPFEM successfully reproduces the directional stress–strain responses and the observed localization morphology, enabling mechanistic interpretation in terms of slip activity and thermomechanical coupling. The simulations indicate that ED loading is dominated by prismatic ⟨a⟩ slip, resulting in lower flow stress and more dispersed strain localization. In contrast, TD loading is governed primarily by pyramidal ⟨c + a⟩ slip, leading to elevated flow stress and intensified localization. The higher ASB sensitivity in the TD orientation is therefore attributed to texture-controlled slip-mode partitioning, enhanced thermomechanical coupling, and a more concentrated crystallographic orientation distribution that facilitates intergranular slip transfer. These findings provide guidance for tailoring microtexture to mitigate dynamic failure in titanium alloys subjected to high-strain-rate loading. Full article

The exceptional mechanical strength and toughness of collagen arise from its well-defined hierarchical architecture. Conventional methods for obtaining collagen aggregates (CAs), such as direct extraction from native tissues or acid swelling followed by mechanical processing, offer limited control over dimensional uniformity and provide little insight into the underlying exfoliation mechanisms. To overcome these challenges, this study introduces a novel strategy that leverages insights into the hierarchical interactions within collagen. We employ the ionic liquid 1-allyl-3-methylimidazolium chloride ([AMIM]Cl) as an exfoliating agent to successfully isolate fibrous CAs from native bovine tendon. By precisely modulating temperature and processing time, we achieve CAs with tunable mesoscale dimensions (diameter 0.9–1.1 μm, length > 160 μm). Molecular dynamics simulations reveal that [AMIM]Cl disrupts the intramolecular hydrogen-bonding network within collagen, thereby facilitating controlled exfoliation. These exfoliated aggregates serve as fundamental building blocks for fabricating collagen films. The resulting materials exhibit robust mechanical integrity, high transparency, reversible pH-responsive behavior, and excellent biocompatibility as verified by cytotoxicity assays, which together underscore their potential as versatile biomaterial platforms. Furthermore, the integration of single-walled carbon nanotubes yields conductive composites with confirmed electrical functionality. This study thus presents an innovative pathway for the precision processing of collagen and advances the design of high-performance collagen-based biomaterials. Full article

While diverse previously fabricated pristine and hydrogenated borophene lattices have been characterized predominantly by their metallic nature, a recent experimental breakthrough has introduced α′–B₈H₄, a semiconducting hydrogenated borophene phase, opening new avenues for boron-based nanoelectronics. Spurred by this breakthrough, herein we utilize a comprehensive first-principles framework to investigate the critical properties of α′–B₈H₄ monolayer. Stability analyses confirm the considerable dynamical and thermal robustness of the α′–B₈H₄ monolayer. Calculations using hybrid functionals show that suspended single-layer α′–B₈H₄ exhibits an indirect semiconducting behavior, with band gaps of 2.06 eV and 2.45 eV predicted by HSE06 and PBE0, respectively. Optical response calculations reveal strong in-plane absorbance in the UV region, with the first notable peak at ~3.65 eV and the main peak occurring between 4.20 and 4.45 eV, both of which are clearly within the ultraviolet range. Mechanical analysis reveals that α′–B₈H₄ exhibits decent in-plane strength (>10 N/m), while phononic transport calculations yield a moderately low room-temperature lattice thermal conductivity of ~20 W/m·K, both displaying slight anisotropic behavior. These results provide a comprehensive first-principles characterization of the α′–B₈H₄ monolayer, highlighting the rare emergence of semiconducting behavior in borophene derivatives and underscoring its potential for UV optoelectronics and nanoscale device applications. Full article

A novel group-drag-anchor system (GDAS), comprising a Delta anchor and a four-tooth anchor, was developed to enhance mooring capacity for floating offshore wind turbines in soft clay seabeds. This study focuses on the influence of the installation method on the embedment performance and dynamic response of the GDAS. Large-deformation finite element analyses were conducted using the coupled Eulerian–Lagrangian (CEL) technique to simulate the installation process under different configurations. A dedicated subroutine was implemented to monitor the evolution of excess pore pressure around the GDAS during the subsequent dynamic loading. Results show that asynchronous installation yields significantly deeper embedment than synchronous installation, especially in seabeds with steep strength gradients. The dynamic response of the GDAS under wave-only, combined wave–current, and mooring-line-failure loading scenarios was further investigated. The asynchronously installed GDAS exhibits considerably more stable long-term performance and lower risk of progressive failure under extreme environmental conditions. This superiority is most evident in clays with a relatively steep strength gradient. These findings provide valuable guidance for the optimal design and installation sequencing of GDASs in engineering practice. Full article

The β grain size in titanium alloys during industrial forging is critical for balancing toughness, cost-effectiveness, and processability. To address the industrial challenge of high cost and difficulty in refining β grains to the tens of micrometers scale, this study investigates the feasibility of achieving a superior strength–ductility balance in TC18 alloy with near-industrial coarse β grains (296~857 μm) under room temperature tension. A pronounced inverse correlation is observed between β grain size and both strength and ductility. The yield strength–grain size relationship follows the Hall–Petch effect, while the anomalous increase in ductility for fine-grained specimens is attributed to three factors. First, smaller grains provide a higher grain boundary density, promoting stress redistribution and mitigating stress concentrations. Second, more uniform stress distribution induces thinner, denser kink bands that enhance plasticity. Third, strain-induced martensite evolves from discrete nanoscale particles to discontinuous lines and ultimately coalesces into continuous planar bands along the (112)β and (110)β planes. This phase transformation, which initiates below a critical grain size of ~500 μm, further alleviates stress concentrations towards slip bands and contributes to dynamic work hardening. The findings demonstrate that coordinated deformation mechanisms enable excellent mechanical performance even in coarse-grained microstructures, providing a practical pathway for optimizing industrial-grade titanium alloys. Full article

This study presents a detailed experimental investigation of the mechanical, fatigue, and dynamic properties of a 3D-printed PA12 CF15 composite at different temperatures. The mechanical properties determined in the temperature range from 23 °C to 120 °C were later implemented in numerical simulations to evaluate the suitability of the material for thermo-mechanical loading conditions. Quasi-static tensile test results revealed a decrease in elastic modulus, yield strength, and ultimate tensile strength with increasing temperature. Fatigue testing demonstrated that increasing load levels lead to reduced durability and a lower maximum number of cycles to failure. Furthermore, elevated testing temperatures caused the composite to exhibit more pronounced plastic behavior, resulting in temperature-dependent fatigue performance. SEM analysis indicated that higher temperatures increase the plasticity of the composite, thereby reducing the reinforcing effect of carbon fibers. The mechanical characteristics obtained experimentally were incorporated into a finite element model, allowing a preliminary assessment of the feasibility of manufacturing an intake manifold from PA12 CF15 using additive manufacturing technology. The results of this study provide valuable data for the design and analysis of dynamically and thermally loaded engineering components produced from PA12 CF15 composites. Full article

Barite sag remains a persistent challenge in water-based drilling fluids, particularly in high-pressure, high-temperature and deviated wellbores where density variations can compromise well control, hole cleaning, well stability and operational safety. Conventional weighting materials often fail to maintain suspension stability under such demanding conditions, highlighting the need for anti-sag solutions. This study presents a systematic evaluation of in-house synthesized barite nanoparticles (26.9–63.2 nm) manufactured using ball milling and incorporated into drilling fluids at concentrations of 0%, 3%, and 5% across densities of 9, 12, and 15 ppg. Using standardized API procedures, the fluids were assessed for rheology, filtration behavior, and sag tendency under both dynamic and static HPHT conditions to mimic realistic drilling environments. Results show that a 5% nanoparticle concentration significantly enhances drilling fluid performance, improving plastic viscosity (up to 50%), yield point (up to 51%), and gel strength (up to 80%), while also reducing fluid loss by 9–10% and mud cake thickness by up to 16%. Moreover, barite sag was substantially mitigated, with dynamic sag reductions of 10–50% and static sag reductions of up to 21% in inclined HPHT conditions. The novelty of this work lies in the comprehensive testing approach, from a practical perspective, covering the effect of an engineered barite nanoparticle to demonstrate a scalable and practical method to enhance sag resistance, suspension stability, and overall drilling efficiency. Full article

Visible Light Positioning (VLP) is widely regarded as a promising technology for high-precision indoor localization due to its immunity to radio-frequency interference and compatibility with existing Light-Emitting Diode (LED) lighting infrastructure. Despite recent progress, current VLP systems remain fundamentally limited by nonlinear received signal strength (RSS) characteristics, unknown transmitter orientations, and dynamic indoor disturbances. Existing solutions typically address these challenges in isolation, resulting in limited robustness and scalability. This paper proposes SCENE-VLP (Sequential Deep Learning with Feature Compression and Optimal State Estimation), a structured positioning framework that integrates feature compression, temporal sequence modeling, and probabilistic state refinement within a unified estimation pipeline. Specifically, SCENE-VLP combines Principal Component Analysis (PCA) and Denoising Autoencoders (DAE) for linear and nonlinear observation conditioning, Gated Recurrent Units (GRU) for modeling temporal dependencies in RSS sequences, and Kalman-based filtering (KF/EKF) for recursive state-space refinement. The framework is formulated as a hierarchical approximation of the nonlinear observation model, linking data-driven measurement learning with Bayesian state estimation. A systematic ablation study across multiple scenarios, including same-dataset evaluation and cross-dataset generalization, demonstrates that each component provides complementary benefits. Feature compression reduces redundancy while preserving dominant signal structure; GRU significantly improves robustness over static regression; and recursive filtering consistently reduces positioning error compared to unfiltered predictions. While both KF and EKF improve performance, EKF provides incremental refinement under mild nonlinearities. Extensive simulations conducted on an indoor dataset collected from a realistic deployment with eight ceiling-mounted LEDs and a single photodetector (PD) show that SCENE-VLP achieves sub-decimeter localization accuracy, with P50 and P95 errors of 1.84 cm and 6.52 cm, respectively. Cross-scenario evaluation further confirms stable generalization and statistically consistent improvements. These results demonstrate that the structured integration of observation conditioning, temporal modeling, and Bayesian refinement yields measurable gains beyond partial pipeline configurations, establishing SCENE-VLP as a robust and scalable solution for next-generation indoor visible light positioning systems. Full article