Search Results (690)

The effect of dislocation pile-ups responsible for the generation or annihilation of dislocations during friction of Ag and Ni was considered. The steady-state friction was accompanied by the formation of twin bundles, intersecting twins, dislocations, adiabatic elongated shear bands, and intense dynamic recrystallization. The mechanisms of microstructural stability and friction instability were analyzed. The theoretical models of dislocation generation and annihilation in nanocrystalline FCC metals in the context of plastic deformation and failure development under friction were proposed. The transition to unstable friction was estimated. The damage of Ag was exhibited in the formation of pores, reducing the contact area and significantly increasing the shear stress. The brittle fracture of Ni represents a catastrophic failure associated with the formation of super-hard nickel oxide. Deformation resistance of the dislocation structures in the mesoscale and macroscale was compared. The coefficient of similitude (K) has been introduced in this work to compare plastic deformation at different scales. The model of the strength–ductility trade-off and microstructural instability is considered. The interaction between the migration of dislocation pile-ups and the driving forces applied to the grain boundaries was estimated. Nanostructure stabilization through the addition of a polycrystalline element (solute) to the crystal interiors in order to reduce the free energy of grain boundary interfaces was investigated. The thermodynamic driving force and kinetic energy barrier involved in strengthening, brittleness, or annealing under plastic deformation and phase formation in alloys and composite materials were examined. Full article

This research presents the results of studies on the physical and mechanical properties of the soil–polymer composites developed by the Scientific and Production Company “Special Polymer Technologies” SPT^® by injecting polyurethane material into clay soils to strengthen the foundations of erected structures. A novel method is proposed to determine the strain characteristics of these composites, embracing the preparation of model specimens in cylindrical containers with subsequent static and dynamic load testing. The results of static tests showed a significant increase in the strain modulus in comparison to that of the soil, resulting in soil stabilization due to a decrease in the initial content of moisture squeezed out of the modified soil. A coefficient of increase in the deformation modulus (K_E) is introduced to quantitatively assess the soil stabilization efficiency. An original technique is also proposed for assessing composite durability, and it is based on analyzing the mass loss after cyclic wetting and drying. The proposed soil stabilization approach promotes and improves digital construction technologies such as Building Information Modeling (BIM) by enabling the accurate simulation and prediction of the behavior of loaded soil in foundation systems. The introduced quantifiable metrics can be integrated into Digital Twin- or BIM-based project planning tools, contributing to sustainability, safety, and reliability in modern construction practices. Full article

The precise mapping of rock joint traces is fundamental to the design and safety assessment of foundations, retaining structures, and underground cavities in building and civil engineering. Existing deep learning approaches either impose prohibitive computational demands for on-site deployment or disrupt the topological continuity of subpixel lineaments that govern rock mass behavior. This study presents BATNet-Lite, a lightweight encoder–decoder architecture optimized for joint segmentation on resource-constrained devices. The encoder introduces a Boundary-Aware Token-Mixing (BATM) block that separates feature maps into patch tokens and directionally pooled stripe tokens, and a bidirectional attention mechanism subsequently transfers global context to local descriptors while refining stripe features, thereby capturing long-range connectivity with negligible overhead. A complementary Multi-Scale Line Enhancement (MLE) module combines depth-wise dilated and deformable convolutions to yield scale-invariant responses to joints of varying apertures. In the decoder, a Skeletal-Contrastive Decoder (SCD) employs dual heads to predict segmentation and skeleton maps simultaneously, while an InfoNCE-based contrastive loss enforces their topological consistency without requiring explicit skeleton labels. Training leverages a composite focal Tversky and edge IoU loss under a curriculum-thinning schedule, improving edge adherence and continuity. Ablation experiments confirm that BATM, MLE, and SCD each contribute substantial gains in boundary accuracy and connectivity preservation. By delivering topology-preserving joint maps with small parameters, BATNet-Lite facilitates rapid geological data acquisition for tunnel face mapping, slope inspection, and subsurface digital twin development, thereby supporting safer and more efficient building and underground engineering practice. Full article

High-Mn steels are commonly fabricated by hot rolling and on-line cooling for cryogenic applications, because there exists an aging embrittlement zone in most high-Mn steels, and this shortcoming makes it difficult to optimize their mechanical properties by heat treatments. Hence, 0.6C-18Mn-0/3/5Al (in wt.%) steels were designed to investigate the effects of Al on their strength and toughness. The addition of 5 wt.% Al can increase yield strength from 357 to 461 MPa and the Charpy impact absorbed energy from 56 to 119 J. Although there is still a cryogenic aging embrittlement zone in each steel, we found that the addition of Al can narrow this brittle zone. Moreover, the absorbed energy is lowered by around 89%, 48%, and 40% for the 0Al, 3Al, and 5Al steels at −196 °C, respectively. Additionally, impact plastic deformation mechanisms were also revealed in the steels with a heat-treating temperature of 600 °C, revealing that the main deformation mechanism shifts from numerous partial dislocation slip to twinning plus strong planar slip as the addition of Al increases. Full article

Sustainable product development demands components that last longer, consume less energy, and can be refurbished within circular supply chains. This study introduces a digital replica-based predictive prototyping workflow for industrial crusher blades that meets these goals. Six commercially used blade geometries (A–F) were recreated as high-fidelity finite-element models and subjected to an identical 5 kN cutting load. Comparative simulations revealed that a triple-edged hooked profile (Blade A) reduced peak von Mises stress by 53% and total deformation by 71% compared with a conventional flat blade, indicating lower drive-motor power and slower wear. To enable fast virtual prototyping and condition-based maintenance, deformation was subsequently predicted using a data-efficient machine-learning model. Multi-view image augmentation enlarged the experimental dataset from 6 to 60 samples, and an XGBoost regressor, trained on computer-vision geometry features and engineering parameters, achieved R² = 0.996 and MAE = 0.005 mm in five-fold cross-validation. Feature-importance analysis highlighted applied stress, safety factor, and edge design as the dominant predictors. The integrated method reduces development cycles, reduces material loss via iteration, extends the life of blades, and facilitates refurbishment decisions, providing a foundation for future integration into digital twin systems to support sustainable product development and predictive maintenance in heavy-duty manufacturing. Full article

Determining orientation relationships between different grains or phases via electron diffraction typically requires coincident zone axes, but it is difficult to achieve in most cases due to tilting angle limitations. To address this challenge, a straightforward method for determining the twinning relationship and twin variant in deformed metals is developed by interpreting the selected area electron diffraction (SAED) patterns and corresponding tilt angles in the transmission electron microscope (TEM). The transformation matrix from the sample coordinate system (SCS) to the crystal coordinate system (CCS) is derived to describe the orientation matrix of the observed target. This method is demonstrated by characterizing twins and corresponding Schmid factors in deformed Ti−15Mo alloy even when the zone axes are not coaxial. This method significantly facilitates the determination of multiple orientation relationships and the quantitative analysis of plastic deformation mechanisms in TEM. Full article

This study investigates the influence of Cu addition on the nanostructural evolution and mechanical performance of a heavily drawn non-equiatomic CoCu_1.71FeMnNi high-entropy alloy (HEA) wire. Through systematic microstructural and compositional analysis, we examine how Cu constituent affects phase separation behavior and promotes deformation-induced nano-twinning in another phase counterpart. The designed HEA wire exhibits an elongated ultrafine dual face-centered cubic (fcc) lamella structure (i.e., Co-Fe-rich and Cu-rich phases) that emerges through compositional segregation by spontaneous phase separation from the as-cast state. High-resolution electron microscopy reveals the dislocation wall boundaries stabilized by nanoscale phase interfaces. The cold-drawn CoCu_1.71FeMnNi wire features an impressive combination of strength and ductility, as well as an ultimate tensile strength of nearly ~2 GPa with an elongation of over ~6%. These findings highlight the critical role of compositional tuning in controlling the ultrafine lamella structure stabilized by spinodal-like phase decomposition, offering a pathway to engineering high-performance HEA wires for advanced structural applications. Full article

The construction environment is a highly dynamic and complex system, presenting challenges for accurately identifying and managing dynamic resources in digital twin-based scenes. This study aims to address the problem of object coordinate distortion caused by camera image deformation, which often reduces the fidelity of dynamic object mapping in digital construction monitoring. A novel dynamic object mapping generation method is proposed to enhance precision and synchronization of dynamic objects within a digital twin environment. The approach integrates internal and external camera parameters, including spatial position, field of view (FOV), and camera pose, into BIM using Dynamo, thereby creating a virtual camera aligned with the physical one. The YOLOv11 algorithm is employed to recognize dynamic objects in real-time camera footage, and corresponding object families are generated in the BIM model. Using perspective projection combined with a linear regression model, the system computes and updates accurate coordinate positions of the dynamic objects, which are then fed back into the camera view to achieve real-time mapping. Experimental validation demonstrates that the proposed method significantly reduces mapping errors induced by lens distortion and provides accurate spatial data, supporting improved dynamic resource perception and intelligent management in digital twin construction environments. Full article

This article investigates the combined effects of different common defects on the structural integrity and operational and environmental safety in the operation of an existing Light Cycle Oil (LCO) storage tank. This study correlates all the tank defects (like corrosion and local plate thinning, deformations, and local stress concentrators) against the loads and their combinations that occur during the tank’s lifetime. All the information gathered by various inspection techniques is used together to create a digital twin of the equipment that will be further analyzed by Finite Element Analysis. A tank condition assessment is a complex activity, and it is based on the experience of the engineer performing it. Since there are multiple methods for performing a comprehensive analysis, starting from the basic visual inspection (which is the most important) and some measurements followed by analytical calculations, up to full wall thickness measurements, 3D scan of deformations and FEA analysis of the tank digital twin, it depends on the engineer performing the evaluation to chose the best method for each particular case from technical and economical point of views. The goal of this article is to demonstrate that analytical and FEA methods have the same result and also to establish a well-determined standard calculation model for future applications. Full article

A (NiCoCr)_99.25C_0.75 medium entropy alloy (MEA) was developed via laser powder bed fusion (LPBF) using pre-alloyed powder feedstock containing 0.75 at%C, followed by a precipitation heat treatment. The as-built alloy exhibited high density (>99.9%), columnar grains, fine substructures, and strong <111> texture. Heat treatment at 700 °C for 1 h promoted the precipitation of Cr-rich carbides (Cr₂₃C₆) along grain and substructure boundaries, which stabilized the microstructure through Zener pinning and the consumption of carbon from the matrix. The heat-treated alloy achieved excellent cryogenic tensile properties at 77 K, with a yield strength of 1230 MPa and an ultimate tensile strength of 1.6 GPa. Compared to previously reported LPBF-built NiCoCr-based MEAs, this alloy exhibited superior strength at both room and cryogenic temperatures, indicating its potential for structural applications in extreme environments. Deformation mechanisms at cryogenic temperature revealed abundant deformation twinning, stacking faults, and strong dislocation–precipitate interactions. These features contributed to dislocation locking, resulting in a work hardening rate higher than that observed at room temperature. This study demonstrates that carbon addition and heat treatment can effectively tune the stacking fault energy and stabilize substructures, leading to enhanced cryogenic mechanical performance of LPBF-built NiCoCr MEAs. Full article

A Digital Twin (DT) is not just a collection of static digital models at the component level of a physical system, but a dynamic entity that evolves in parallel with the physical system it mirrors. This evolution starts with physics-based or data-driven physics models representing the physical system and advances to Authoritative Virtualization or DT through continuous data assimilation, and ongoing Digital Engineering (DE) Test and Evaluation (T&E) processes. This paper presents a generalizable mathematical framework for the DE Test and Evaluation Process that incorporates data assimilation, uncertainty quantification, propagation, and DT calibration, applicable to diverse physical–digital systems. This framework will enable the DT to perform operations, control, decision-making, and predictions at scale. The framework will be implemented for two cases: (i) the DT of the CubeSat to analyze the CubeSat’s structural deformation during its deployment in space and (ii) the DT of the CROME engine. The DT of the CubeSat will be capable of predicting and monitoring structural health during its space operations. The DT of the CROME engine will be able to predict the thrust at various conditions. Full article

Creating high-fidelity digital twins (DTs) for Industry 4.0 applications, it is fundamentally reliant on the accurate 3D modeling of physical assets, a task complicated by the inherent imperfections of real-world point cloud data. This paper addresses the challenge of reconstructing accurate, watertight, and topologically sound 3D meshes from sparse, noisy, and incomplete point clouds acquired in complex industrial environments. We introduce a robust two-stage completion-to-reconstruction framework, C2R3D-Net, that systematically tackles this problem. The methodology first employs a pretrained, self-supervised point cloud completion network to infer a dense and structurally coherent geometric representation from degraded inputs. Subsequently, a novel adaptive surface reconstruction network generates the final high-fidelity mesh. This network features a hybrid encoder (FKAConv-LSA-DC), which integrates fixed-kernel and deformable convolutions with local self-attention to robustly capture both coarse geometry and fine details, and a boundary-aware multi-head interpolation decoder, which explicitly models sharp edges and thin structures to preserve geometric fidelity. Comprehensive experiments on the large-scale synthetic ShapeNet benchmark demonstrate state-of-the-art performance across all standard metrics. Crucially, we validate the framework’s strong zero-shot generalization capability by deploying the model—trained exclusively on synthetic data—to reconstruct complex assets from a custom-collected industrial dataset without any additional fine-tuning. The results confirm the method’s suitability as a robust and scalable approach for 3D asset modeling, a critical enabling step for creating high-fidelity DTs in demanding, unseen industrial settings. Full article

Twinning-induced plasticity (TWIP) steels represent a significant development in automotive steel production, characterized by advanced strength and ductility properties. The present study empirically investigated the effects of process parameters on the cutting process and surface quality of TWIP980 steel sheet by abrasive water jet (AWJ) cutting. The cutting experiments were conducted on 1.4 mm thick sheet metal using four different traverse speeds (50, 100, 200, and 400 mm/min) and four different water jet pressures (1500, 2000, 2500, and 3000 bar). Two different abrasive flow rates (300 and 600 g/min) were also utilized. The cut surfaces were characterized in three dimensions with an optical profilometer. The parameters of surface roughness, kerf width, taper angle, and material removal rate (MRR) were determined. Furthermore, microhardness measurements were conducted on the cut surfaces. The optimal surface quality and geometrical accuracy were achieved by applying a combination of parameters, including 3000 bar of pressure, a traverse rate of 400 mm/min, and an abrasive flow rate of 600 g/min. Concurrently, an effective cutting performance with increased MRR and reduced taper angles was achieved under these conditions. The observed increase in microhardness with increasing pressure is attributable to a hardening effect resulting from local plastic deformation. Full article

This study presents a methodology for developing and validating digital models of tooth-inlay systems, aiming to trace the complete workflow from clinical procedures to simulation by involving dental professionals—dentists for manual cavity preparation and dental technicians for restoration modelling—while integrating micro-computed tomography (micro-CT) imaging with finite element analysis (FEA). The proposed workflow includes (1) the acquisition of high-resolution 3D micro-CT scans of a non-restored tooth, (2) image segmentation and reconstruction to create anatomically accurate digital twins and mesh generation, (3) the selection of proper resin and the 3D printing of four typodonts, (4) the manual preparation of cavities on the typodonts, (5) the acquisition of high-resolution 3D micro-CT scans of the typodonts, (6) mesh generation, digital inlay and onlay modelling and material property assignment, and (7) nonlinear FEA simulations under representative masticatory loading. The approach enables the visualisation of stress and deformation patterns, with preliminary results indicating stress concentrations at the tooth-restoration interface integrating different cavity alternatives and restorations on the same tooth. Quantitative outputs include von Mises stress, strain energy density, and displacement distribution. This study demonstrates the feasibility of using image-based, tooth-specific digital twins for biomechanical modelling in dentistry. The developed framework lays the groundwork for future investigations into the optimisation of restoration design and material selection in clinical applications. Full article

As vital material carriers of human civilization, earthen sites are experiencing continuous surface deterioration under the combined effects of weathering and anthropogenic damage. Traditional surface conservation techniques, due to their poor compatibility and limited reversibility, struggle to address the compound challenges of micro-scale degradation and macro-scale deformation. With the deep integration of digital twin technology, spatial information technologies, intelligent systems, and sustainable concepts, earthen site surface conservation technologies are transitioning from single-point applications to multidimensional integration. However, challenges remain in terms of the insufficient systematization of technology integration and the absence of a comprehensive interdisciplinary theoretical framework. Based on the dual-core databases of Web of Science and Scopus, this study systematically reviews the technological evolution of surface conservation for earthen sites between 2000 and 2025. CiteSpace 6.2 R4 and VOSviewer 1.6 were used for bibliometric visualization analysis, which was innovatively combined with manual close reading of the key literature and GPT-assisted semantic mining (error rate < 5%) to efficiently identify core research themes and infer deeper trends. The results reveal the following: (1) technological evolution follows a three-stage trajectory—from early point-based monitoring technologies, such as remote sensing (RS) and the Global Positioning System (GPS), to spatial modeling technologies, such as light detection and ranging (LiDAR) and geographic information systems (GIS), and, finally, to today’s integrated intelligent monitoring systems based on multi-source fusion; (2) the key surface technology system comprises GIS-based spatial data management, high-precision modeling via LiDAR, 3D reconstruction using oblique photogrammetry, and building information modeling (BIM) for structural protection, while cutting-edge areas focus on digital twin (DT) and the Internet of Things (IoT) for intelligent monitoring, augmented reality (AR) for immersive visualization, and blockchain technologies for digital authentication; (3) future research is expected to integrate big data and cloud computing to enable multidimensional prediction of surface deterioration, while virtual reality (VR) will overcome spatial–temporal limitations and push conservation paradigms toward automation, intelligence, and sustainability. This study, grounded in the technological evolution of surface protection for earthen sites, constructs a triadic framework of “intelligent monitoring–technological integration–collaborative application,” revealing the integration needs between DT and VR for surface technologies. It provides methodological support for addressing current technical bottlenecks and lays the foundation for dynamic surface protection, solution optimization, and interdisciplinary collaboration. Full article