Search Results (99)

Additive Manufacturing (AM) has attracted considerable interest over the past three decades, driven by growing industrial demand. Among metal AM techniques, Wire and Arc Additive Manufacturing (WAAM), a Directed Energy Deposition (DED) variant, has emerged as a prominent method for producing large-scale components with high deposition rates and cost efficiency. However, WAAM parts typically exhibit rough surface profiles, which can induce stress concentrations and promote fatigue crack initiation under cyclic loading. This study presents an integrated experimental and numerical investigation into the fatigue performance of as-built WAAM steel. Fatigue specimens extracted from a WAAM-fabricated wall were tested under cyclic loading, followed by fractography to assess the influence of surface irregularities and subsurface defects on fatigue behaviour. Surface topography analysis identified critical stress-concentration regions and key surface roughness parameters. Additionally, 3D scanning was used to reconstruct the specimen topography, enabling detailed 2D and 3D finite element (FE) modelling to analyze stress distribution along the as-built surface and predict fatigue life. A Smith-Watson-Topper (SWT) critical plane-based approach was applied for multiaxial fatigue life estimation. The results reveal a good correlation between experimental fatigue data and numerically predicted results, validating the proposed combined methodology for assessing durability of as-built WAAM components. Full article

Accurate prediction of soil–structure interface shear strength (τ_max) is critical for reliable geotechnical design. This study combines experimental testing with interpretable machine learning to overcome the limitations of traditional empirical models and black-box approaches. Ninety large-displacement ring shear tests were performed on five sands and three interface materials (steel, PVC, and stone) under normal stresses of 25–100 kPa. The results showed that particle morphology, quantified by the regularity index (RI), and surface roughness (R_t) are dominant factors. Irregular grains and rougher interfaces mobilised higher τ_max through enhanced interlocking, while smoother particles reduced this benefit. Harder surfaces resisted asperity crushing and maintained higher shear strength, whereas softer materials such as PVC showed localised deformation and lower resistance. These experimental findings formed the basis for a hybrid symbolic regression framework integrating Genetic Programming (GP) with Shapley Additive Explanations (SHAP), Fourier feature augmentation, and physics-informed constraints. Compared with multiple linear regression and other hybrid GP variants, the Physics-Informed Neural Fourier GP (PIN-FGP) model achieved the best performance (R² = 0.9866, RMSE = 2.0 kPa). The outcome is a set of five interpretable and physics-consistent formulas linking measurable soil and interface properties to τ_max. The study provides both new experimental insights and transparent predictive tools, supporting safer and more defensible geotechnical design and analysis. Full article

Autonomous planetary rovers require robust path planning over rough 3D terrains, where traditional metrics such as path length, number of nodes, and planning time do not adequately capture path quality. Rapidly Exploring Random Trees (RRT) and its asymptotically optimal variant, RRT*, are widely used sampling-based algorithms for non-holonomic mobile robots but are limited when traversing uneven 3D terrain. This study proposes 3D-RRT*, a simplified, terrain-aware extension of Traversability-Based RRT*, designed to maintain high path quality while reducing planning time. The performance of 3D-RRT* is evaluated using metrics that are both practical and meaningful in the context of planetary rover path planning: path smoothness, path flatness, path length, and planning time. Exploration of a simulated Martian surface demonstrates that 3D-RRT* significantly improves path quality compared to standard RRT and RRT*, achieving smoother, safer, and more efficient routes for planetary rover missions. Full article

The rapid growth of e-commerce has created substantial environmental impacts, driving the need for advanced optimization models to enhance supply chain sustainability. As consumer preferences shift toward environmental responsibility, organizations must adopt robust quantitative methods to reduce ecological footprints while ensuring operational efficiency. This study develops a novel hybrid multi-criteria decision-making (MCDM) model to evaluate and prioritize green suppliers under uncertainty, integrating the rough-Dombi best–worst method (BWM) and an improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The proposed model addresses two key challenges: (1) inconsistency in expert judgments through rough set theory and Dombi aggregation operators and (2) ranking instability via an enhanced TOPSIS formulation that mitigates rank reversal. Mathematically, the rough-Dombi BWM leverages interval-valued rough numbers to model subjective expert preferences, while the Dombi operator ensures flexible and precise weight aggregation. The modified TOPSIS incorporates a dynamic distance metric to strengthen ranking robustness. A case study of five e-commerce suppliers validates the model’s effectiveness, with results identifying cost, green competitiveness, and external environmental management as the dominant evaluation dimensions. Key indicators—such as product price, pollution control, and green design—are rigorously prioritized using the proposed framework. Theoretical contributions include (1) a new rough-Dombi fusion for criteria weighting under uncertainty and (2) a stabilized TOPSIS variant with reduced sensitivity to data perturbations. Practically, the model provides e-commerce enterprises with a computationally efficient tool for sustainable supplier selection, enhancing resource allocation and green innovation. This study advances the intersection of uncertainty modeling, operational research, and sustainability analytics, offering scalable methodologies for mathematical decision-making in supply chain contexts. Full article

Graph theory models relationships by representing entities as vertices and their interactionsas edges. To handle directionality and multiple head–tail assignments, various extensions—directed, bidirected, and multidirected graphs—have been introduced, with the multidirected graph unifying the first two. In this work, we further enrich this landscape by proposing the Multidirected hypergraph, which merges the flexibility of hypergraphs and superhypergraphs to describe higher-order and hierarchical connections. Building on this, we introduce five uncertainty-aware Multidirected frameworks—fuzzy, neutrosophic, plithogenic, rough, and soft multidirected graphs—by embedding classical uncertainty models into the Multidirected setting. We outline their formal definitions, examine key structural properties, and illustrate each with examples, thereby laying groundwork for future advances in uncertain graph analysis and decision-making. Full article

This study investigates supersonic flow within a nozzle under low-pressure conditions at the continuum mechanics boundary. This phenomenon is commonly encountered in applications such as the differentially pumped chamber of an Environmental Scanning Electron Microscope (ESEM), which employs an aperture to separate two regions with a great pressure gradient. The nozzle geometry and flow control in this region can significantly influence the scattering and loss of the primary electron beam traversing the differentially pumped chamber and aperture. To this end, an experimental chamber was designed to explore aspects of this low-pressure regime, characterized by a varying ratio of inertial to viscous forces. The initial experimental results obtained using pressure sensors from the fabricated experimental chamber were utilized to refine the Ansys Fluent simulation setup, and in this combined approach, initial analyses of supersonic flow and shock waves in low-pressure environments were conducted. The refined Ansys Fluent system demonstrated a very good correspondence with the experimental findings. Subsequently, an analysis of the influence of surface roughness on the resulting flow behavior in low-pressure conditions was performed on this refined model using the refined CFD model. Based on the obtained results, a comparison of the influence of nozzle roughness on the resulting electron beam scattering was conducted for selected low-pressure variants relevant to the operational conditions of the Environmental Scanning Electron Microscope (ESEM). The influence of roughness at elevated working pressures within the ESEM operating regime on reduced electron beam scattering has been demonstrated. At lower pressure values within the ESEM operating regime, this influence is significantly diminished. Full article

Due to climate change, the electric vehicle (EV) industry is rapidly growing and drawing researchers interest. Driving conditions like mountainous roads, slick surfaces, and rough terrains illuminate the vehicles inherent nonlinearities. Under such scenarios, the behavior of power sources (fuel cell, battery, and super-capacitor), power processing units (converters), and power consuming units (traction motors) deviates from nominal operation. The increasing demand for FCHEVs necessitates control systems capable of handling nonlinear dynamics, while ensuring robust, precise energy distribution among fuel cells, batteries, and super-capacitors. This paper presents a DSMC strategy enhanced with Robust Uniform Exact Differentiators for FCHEV energy management. To optimally tune DSMC parameters, reduce chattering, and address the limitations of conventional methods, a hybrid metaheuristic framework is proposed. This framework integrates moth flame optimization (MFO) with the gravitational search algorithm (GSA) and Fractal Heritage Evolution, implemented through three spiral-based variants: MFOGSAPSO-A (Archimedean), MFOGSAPSO-H (Hyperbolic), and MFOGSAPSO-L (Logarithmic). Control laws are optimized using the Integral of Time-weighted Absolute Error (ITAE) criterion. Among the variants, MFOGSAPSO-L shows the best overall performance with the lowest ITAE for the fuel cell (56.38), battery (57.48), super-capacitor (62.83), and DC bus voltage (4741.60). MFOGSAPSO-A offers the most accurate transient response with minimum RMSE and MAE FC (0.005712, 0.000602), battery (0.004879, 0.000488), SC (0.002145, 0.000623), DC voltage (0.232815, 0.058991), and speed (0.030990, 0.010998)—outperforming MFOGSAPSO, GSA, and PSO. MFOGSAPSO-L further reduces the ITAE for fuel cell tracking by up to 29% over GSA and improves control smoothness. PSO performs moderately but lags under transient conditions. Simulation results conducted under EUDC validate the effectiveness of the MFOGSAPSO-based DSMC framework, confirming its superior tracking, faster convergence, and stable voltage control under transients making it a robust and high-performance solution for FCHEV. Full article

Lithium disilicate ceramics (LDSs) are widely used in restorative dentistry for their excellent aesthetic and mechanical properties. Variants like zirconia-reinforced lithium silicate (ZLS) and advanced lithium disilicate (ALD) were developed to enhance these characteristics. However, differences in their physical and optical properties, as well as the influence of processing techniques (heat pressing vs. CAD-CAM), remain unclear. This study aimed to evaluate the physical and aesthetic properties of LDS, ZLS, and ALD ceramics. A systematic review and meta-analysis following PRISMA guidelines were conducted. Studies published in the last ten years were retrieved from PubMed, Web of Science, Scopus, Cochrane, and Scielo. The inclusion criteria encompassed in vitro studies analyzing LDS, ZLS, and ALD ceramics with quantitative data on mechanical and aesthetic properties. Meta-analyses were performed using a random-effects model, with subgroup analyses based on ceramic type and processing technique. Twenty-two studies met the inclusion criteria. Meta-analyses showed significant differences in flexural strength, hardness, surface roughness, wear, and translucency. The processing technique influenced these properties, with CAD-CAM materials exhibiting distinct performance compared to heat-pressed ceramics. Publication bias was assessed using Egger’s test and the Trim and Fill method, and heterogeneity via meta-regression. LDS showed the highest fracture resistance and least wear, while ALD had greater roughness depth. Heat pressing enhanced hardness and reduced roughness, whereas CAD-CAM improved flexural strength. Considering these findings and study limitations, LDS appears the most suitable option for clinical use due to its superior mechanical performance. Full article

With the rapid development of urban construction, the demand for safety monitoring of reinforced concrete structures has been increasing. However, current crack detection methods still struggle with limited accuracy, poor real-time performance, and difficulty recognizing extremely small or low-contrast cracks in complex environments. To address these challenges, this study proposes a new method that combines the improved Visual Geometry Group Network 16, U-Net, and You Only Look Once target detection technologies. A new model for detecting concrete corrosion cracks has been developed based on this method. After 100 training epochs, the model achieved a precision of 94.4% and a loss rate of 2.6%, with an average Intersection over Union exceeding 85.0%. In high-roughness field tests, the proposed model achieved a crack width detection error of ±4.0 mm. For cracks that were soil-covered or partially occluded, the detection errors were ±5.4 mm and ±5.1 mm, respectively. Based on the original model, two additional lightweight variants were constructed, with the inference speeds of the three models recorded as 36 ms, 28 ms, and 24 ms in descending order. The results demonstrate that the proposed detection model offers an efficient and intelligent solution for structural health monitoring, with strong potential for engineering applications and urban infrastructure renewal. However, the model still presents a risk of misclassification when identifying fine cracks under low-contrast or complex background conditions. Future work will incorporate adaptive image enhancement and more refined feature extraction algorithms to further improve detection robustness and real-time performance. Full article

The surface profile and structural alignment of fibers and yarns in fabrics are critical factors affecting the electrical properties of conductive textile surfaces. This study aimed to investigate the impact of fabric surface roughness and the geometrical parameters of woven fabrics on their electrical resistance properties. Surface roughness was assessed using the MicroSpy^® Profile profilometer FRT (Fries Research & Technology) Metrology™, while electrical resistance was evaluated using the Van der Pauw method. The findings indicate that rougher fabric surfaces exhibit higher electrical resistance due to surface irregularities and lower yarn compactness. In contrast, smoother fabrics improve conductivity by enhancing surface uniformity and yarn contact. Fabric density, particularly weft density, governs the structural alignment of yarns. A 35% increase in weft density (W19–W27) resulted in a 13–15% reduction in resistance, confirming that denser fabrics facilitate current flow. Higher weft density also increases directional resistance differences, enhancing anisotropic behavior. Angular distribution analysis showed lower resistance and greater anisotropy at perpendicular orientations (0° and 180°, the weft direction; 90° and 270°, the warp direction), while diagonal directions (45°, 135°, 225°, and 315°) exhibited higher resistance. Surface roughness further hindered current flow, whereas increased weft density and surface mass reduced resistance and improved the directional dependencies of the electrical resistances. This analysis was conducted based on research using woven fabrics produced from silver-plated polyamide yarns (Shieldex^® 117/17 HCB). These insights support the optimization of these conductive fabrics for smart textiles, wearable sensors, and e-textiles. Fabric variants W19 and W21, with lower resistance variability and better isotropic behavior under the S electrode arrangement, could be proposed as suitable materials for integration into compact sensing systems like heart rate or bio-signal monitors. Full article

Objectives: To examine the effects of surface treatments on the color stability, surface roughness, surface gloss, and wettability of monolithic polychromatic material jetting (MJT) 3D-printed denture material. Material and Methods: Twenty-one color variants of the same denture material (TrueDent; Stratasys, Eden, MN, USA) underwent two surface treatments (polishing only or polishing and glazing), creating 42 study groups with a total of 420 samples (n = 10 per group). The samples were manufactured using a PolyJet 3D printer (J5 DentaJet; Stratasys, Eden, MN, USA), a type of MJT 3D printer. Color measurements were taken with a digital spectrophotometer before and after the surface treatments, and quantitative color differences (ΔE₀₀ and ΔC*) were calculated using the CIE2000 system. Comparisons of ΔE₀₀ were made against the 50%:50% acceptability threshold (AT) of 1.8 and the 50%:50% perceptibility threshold (PT) of 0.8 for tooth shade, as well as the 50%:50% PT of 1.72 and the 50%:50% AT of 4.08 for gingival (pink) shade. After surface treatment, the gloss was measured using a glossmeter, surface roughness was measured with optical profilometry, and wettability was measured by contact angle measurements using an optical tensiometer. The significance of surface treatment on color changes for each color variant was evaluated using one-sided, one-sample t-tests against the AT and PT. The effects of surface treatment on surface gloss, surface roughness, contact angle, and ΔC* were analyzed using t-tests for each color variant. Pairwise comparisons between groups were made using Fisher’s Protected Least Significant Differences (α = 0.05). Results: In most cases, glazing caused the color change (ΔE₀₀) to exceed the AT and PT, with a few exceptions. Most materials exhibited a more vibrant (more saturated) appearance and statistically higher chroma, with glazed surface treatments compared to polished ones, though there were some exceptions. For all materials, the glazed samples had significantly higher gloss units than the polished ones (p < 0.0001). Additionally, all materials showed significantly higher surface roughness in glazed samples compared to polished ones (p < 0.0001 for most). The polished samples had significantly higher contact angles (p < 0.0001 for most). Conclusions: Surface treatments significantly influenced the color, surface gloss, surface roughness, and wettability of MJT 3D-printed denture materials. Glazing led to increased chroma and gloss and produced more hydrophilic surfaces, although it also increased surface roughness. These results highlight the importance of surface treatment selection in optimizing the clinical performance of MJT-fabricated dentures. Full article

Implant-associated infections, particularly those linked to Staphylococcus aureus (S. aureus), continue to compromise the clinical success of β-tricalcium phosphate (β-TCP) implants despite their excellent biocompatibility and osteoconductivity. This investigation aims to tackle these challenges by integrating femtosecond (fs)-laser surface processing with two complementary strategies: ion doping and functionalization with green-synthesized silver nanoparticles (AgNPs). AgNPs were produced via fs-laser photoreduction using green tea leaf extract (GTLE), noted for its anti-inflammatory and antioxidant properties. Fs-laser processing was applied to modify β-TCP scaffolds by systematically varying scanning velocities, fluences, and patterns. Lower scanning velocities generated organized nanostructures with enhanced roughness and wettability, as confirmed by scanning electron microscopy (SEM), optical profilometry, and contact angle measurements, whereas higher laser energies induced significant phase transitions between hydroxyapatite (HA) and α-tricalcium phosphate (α-TCP), as revealed by X-ray diffraction (XRD). AgNP-functionalized scaffolds demonstrated markedly superior antibacterial activity against S. aureus compared to the ion-doped variants, attributed to the synergistic interplay of nanostructure-mediated surface disruption and AgNP-induced bactericidal mechanisms. Although ion-doped scaffolds exhibited limited direct antibacterial effects, they showed concentration-dependent activity in indirect assays, likely due to controlled ion release. Both strategies promoted osteogenic differentiation of human bone marrow mesenchymal stem cells (hBM-MSCs) under defined conditions, albeit with transient cytotoxicity at higher fluences and excessive ion doping. Overall, this approach holds promise for markedly improving antibacterial efficacy and osteogenic compatibility, potentially transforming bone regeneration therapies. Full article

Laser shock peening (LSP) significantly enhances fatigue and corrosion resistance, especially in additively manufactured components. This effect is stronger when confinement is used; typically, it is water. However, water poses risks to sensitive electronics. As an alternative, this study explored gel-based confinement. A Ni-based alloy was LSP-treated using 532 nm and 1064 nm wavelengths, with three types of gel compared to water as a control. The results showed that gel confinement can induce compressive residual stresses and increase surface microhardness. However, gels were generally less effective than water in terms of residual stress magnitude and depth of hardening. Additionally, gel confinement required the use of a 1064 nm laser, whereas water confinement was more effective with 532 nm. Among the gels tested, one adhesive variant performed best due to improved surface contact and strong adhesion. The observed increase in microhardness and compressive stress was linked to surface grain refinement and twinning. Overall, adhesive gels offer potential benefits for LSP, particularly for additively manufactured parts, which often have high surface roughness and require non-conductive confinement solutions. Full article

The construction of artificial microorganisms often relies on the transfer of genomes from donor to acceptor cells. This synthetic biology approach has been considerably fostered by the J. Craig Venter Institute but apparently depends on the use of microorganisms, which are very closely related. One reason for this limitation of the “creative potential” of “classical” transformation is the requirement for adequate “fitting” of newly synthesized polypeptide components, directed by the donor genome, to interacting counterparts encoded by the pre-existing acceptor genome. Transformation was introduced in 1928 by Frederick Griffith in the course of the demonstration of the instability of pneumococci and their conversion from rough, non-pathogenic into smooth, virulent variants. Subsequently, this method turned out to be critical for the identification of DNA as the sole matter of inheritance. Importantly, the initial experimental design (1.0) also considered the inheritance of both structural (e.g., plasma membranes) and cybernetic information (e.g., metabolite fluxes), which, in cooperation, determine topological and cellular heredity, as well as fusion and blending of bacterial cells. In contrast, subsequent experimental designs (1.X) were focused on the use of whole-cell homogenates and, thereafter, of soluble and water-clear fractions deprived of all information and macromolecules other than those directing protein synthesis, including outer-membrane vesicles, bacterial prions, lipopolysaccharides, lipoproteins, cytoskeletal elements, and complexes thereof. Identification of the reasons for this narrowing may be helpful in understanding the potential of transformation for the creation of novel microorganisms. Full article

This study refers to the application of an advanced tool in the form of numerical modelling in order to develop a low-waste hot die forging technology to produce a connecting rod forging. The technology aims at ensuring a limited amount of the charge material is necessary to produce one forging, as well as minimizing forging forces, and thus the electric energy consumption. The study includes a verification of the current production technology, which constituted the basis for the construction and development of a numerical model. A new construction of the forging tools was developed, with an additional pre-roughing pass (0X). The new process consists of die forging in the pre-roughing pass (0X), the roughing pass (1X) and the finishing impression (2X). Numerical modelling was subsequently conducted with the use of the Forge 3.0 NxT software. A detailed analysis was conducted on the accuracy of the tool impression filling (including the pre-roughing pass) by the deformed material, the distribution of temperatures for the forgings and the plastic deformations, as well as the courses of forging forces and energy. The results were verified under industrial conditions and compared with the forgings obtained in the previous technology (a roughing pass and a finishing impression). As a result of introducing the pre-roughing pass 0X, the forces were distributed between three impressions, including the especially developed pre-roughing pass. It was confirmed that the abovementioned changes in terms of forging tool construction had a positive effect on relieving the roughing pass and the finishing impression as well as limiting the charge material, and they also lowered the process energy consumption by 10%. This study also validated the relevance of using FE modelling to verify processes under virtual conditions before being implemented under industrial conditions. Therefore, the proposed approach based on multi-variant numerical simulations can be successfully used to improve other manufacturing processes in terms of reducing energy and material consumption and increasing tool service life. Full article