Search Results (605)

A non-contact laser polishing method for additively manufactured polymer components with complex three-dimensional geometries is presented, employing a 6-axis robotic system. Robot-guided sample orientation, a quasi-top-hat scanning strategy, and closed-loop temperature control are combined to address curved geometries. On Selective Laser Sintering (SLS)-manufactured Polyamide 12 (PA12) tensile samples with three build orientations and two thicknesses, laser polishing yields up to a 15% increase in tensile strength (Rm) and a 50% increase in elongation at break (A). For 45°-built 5 mm samples, Rm increases from 31.53 MPa to 36.33 MPa and A from 6.52% to 9.8%, approaching the tensile strength reported for optimally oriented SLS-printed PA12 Smooth samples of the same grade. For convex–concave PA12 demonstrators, areal roughness (Sa) on convex surfaces is reduced from 33.6 µm to 2.7 µm (approximately 92%) and the high-pass-filtered micro-roughness (Sa_HP) on concave surfaces by 98.2% to 0.15 µm. For Fused Deposition Modeling (FDM)-printed Polyaryletherketone (PAEK) samples, Sa is reduced from 28.35 µm to 4.1 µm and Sa_HP from 15.98 µm to 0.23 µm (98.6%), despite the high melting temperature and anisotropic raster topography. These results demonstrate that robotic laser polishing constitutes a viable post-processing approach for functionally demanding polymer applications. Full article

Understanding forest dynamics requires reliable inventories that assess tree- and stand-level characteristics. Traditionally, this has relied on field measurements such as diameter at breast height (DBH), height, and crown attributes, but these methods are labor-intensive and spatially limited. Remote sensing, particularly Light Detection and Ranging (LiDAR), has expanded forest inventory capacity by generating three-dimensional structural information. Mobile laser scanning (MLS), a recent adaptation, offers flexible, high-resolution data collection, though its performance across complex forests is still being evaluated. This study assessed the effectiveness of MLS in detecting individual trees and estimating DBH in mixed-species forests of the Northeastern United States. We also evaluated the influence of tree- and plot-level characteristics on detection accuracy and DBH estimation. Results showed an 85.2% tree detection rate, a 23.5% commission rate, and a DBH root mean square error (RMSE) of 1.98 cm (9.65%). Among the variables tested, tree DBH was the only significant predictor of detection probability; tree density and relative density had minimal effect. These findings demonstrate that MLS can achieve precise DBH estimation when trees are correctly identified, but false detections remain a limitation. Further methodological improvements are needed to enhance accuracy in structurally complex forests and advance MLS for operational forest monitoring. Full article

This study scientifically assessed the safety of the Ming Dynasty official-style timber structure of Taiyuan Chongshan Temple’s Great Mercy Hall, a nationally protected cultural relic. An integrated framework was adopted, including form restoration via 3D laser scanning and manual surveying, damage detection using impedance meters, stress wave tomography and one-dimensional stress wave testing, mechanical analysis with a differentiated material finite element model, and short-term on-site monitoring at risk points. Results showed that the 303.3 mm construction ruler length was restored, with the column grid tilting northwestward; the main structure was hardwood pine, and critical columns had severe localized damage (24% internal damage rate, 13% cross-sectional damage ratio) with 42% residual strength in some members; and the structure remained elastically safe, with material degradation causing 6.3–13.3% linear displacement amplification. Two weak links (eave purlin deflection: 33–37 mm; double-eave golden column axial force concentration: 86.9–88.5 kN) and dougong’s outward inclination due to eccentric compression were identified. Short-term monitoring indicated temperature-driven elastic responses and an 8 mm cumulative residual displacement in the northern single-step beam, and a three-level early warning threshold system was proposed. This study clarified the hall’s state as “overall stable with localized weaknesses”, providing a methodological reference for the preventive protection of similar ancient timber structures. Full article

Prefabricated steel structures have been increasingly adopted in modern construction due to their high efficiency, sustainability, and industrialized production. However, their construction quality and efficiency are often compromised by accumulated geometric deviations during fabrication, transportation, assembly, and welding, while traditional construction control and welding processes remain highly dependent on manual measurements and empirical operations. To address these challenges, this study proposes a digital construction framework for prefabricated steel structures, integrating high-precision three-dimensional (3D) laser scanning, Building Information Modeling (BIM), and intelligent welding technologies. First, high-precision 3D laser scanning is employed to capture the as-built geometric information of prefabricated steel components, generating dense point cloud data for construction-stage deviation detection and quantitative comparison with BIM-based design models. Based on deviation analysis, a digital construction control strategy is established to support real-time feedback, error compensation, and assembly adjustment. An engineering case study involving a complex prefabricated steel structure is conducted to validate the proposed framework. The results demonstrate that the integrated digital construction and intelligent welding approach significantly improves assembly accuracy, weld positioning precision, and construction efficiency, while reducing manual intervention and error accumulation. Overall, this study contributes to the body of knowledge by proposing a unified closed-loop digital construction paradigm that integrates geometric perception, deviation-driven decision-making, and intelligent welding execution, thereby bridging the gap between construction control and robotic fabrication in prefabricated steel structures. Full article

Fused deposition modeling (FDM)-based three-dimensional (3D) fabrication offers a viable approach to manufacturing highly customized carbon fiber-reinforced polyether ether ketone (CFR-PEEK) components with complex geometries. However, the mechanical properties and surface roughness of FDM-fabricated parts are strongly influenced by processing parameters, particularly layer thickness. This study investigates the influence of layer thickness (0.1 mm and 0.2 mm) on the surface roughness, crystallinity, mechanical properties, and morphological characteristics of FDM-printed 10% CFR-PEEK specimens. The specimens were characterized using mechanical testing, differential scanning calorimetry (DSC), confocal laser microscopy, X-ray micro-computed tomography (µCT), and scanning electron microscopy (SEM). The results show that specimens printed with a 0.2 mm layer thickness exhibit higher crystallinity and ball indentation hardness while also showing increased surface roughness and porosity, with µCT analysis revealing larger and more spatially clustered voids near the sub-perimeter regions. In contrast, specimens printed with a 0.1 mm layer thickness demonstrate higher tensile strength, elastic modulus, elongation at break, and compressive stress. SEM fractography further indicates improved interlayer bonding and a relatively cohesive fracture surface in specimens printed with a 0.1 mm layer thickness. These findings demonstrate clear layer-thickness-dependent processing–structure–property relationships in FDM-printed CFR-PEEK composites and provide guidance for optimizing printing parameters to achieve improved mechanical performance. Full article

Despite its potential to enhance construction quality, efficiency, and sustainability, modular construction continues to experience defects that hinder its broader adoption. Understanding and mitigating defects is essential for maximising the sustainability benefits of modular construction by reducing material waste, minimising rework and improving lifecycle performance. Existing research remains fragmented, with limited synthesis integrating defects with their root causes across the project lifecycle. To address this gap, this study investigates defect types, lifecycle-based causes, and mitigation strategies in modular building projects through a PRISMA-guided systematic literature review of 61 peer-reviewed journal articles published between 2015 and 2025 and retrieved from Scopus and Web of Science. Six major defect categories were identified: geometric and dimensional; material and component; joint and connection integrity; envelope performance and durability; structural; and mechanical, electrical, and plumbing (MEP) defects, with geometric and dimensional defects emerging as the most prevalent, accounting for 26.7% of reported cases. Lifecycle root-cause mapping indicates that poor workmanship during on-site assembly is the dominant contributor, accounting for 44.1% of identified root causes, with manufacturing errors (26.8%) and design limitations (13.4%) acting as critical upstream sources. Mitigation strategies cluster into three groups: general recommendations (39% of reported strategies), mainly focusing on low-cost organisational measures such as logistics coordination and workforce training; structured risk-management frameworks (9.1%), including assembly sequencing and tolerance planning; and digital and data-driven technologies (51.9%), such as laser scanning, AI-based inspection, and digital twins, enabling proactive quality assurance across the lifecycle. The study proposes an integrated lifecycle–defect–mitigation framework to strengthen quality governance and advance sustainable modular delivery. Full article

Laser-induced microjet-assisted ablation is an emerging technology in the field of laser processing. However, the influence of solid boundaries on jet behavior and the associated material removal mechanism remains unclear after observing and analyzing the ablation process. To address this, the present study systematically investigates the effect of the incidence angle on the processing efficiency and material removal mechanism in laser-induced microjet ablation. By controlling the laser power and liquid layer thickness, the dynamic behavior of the microjet, material removal performance, and surface morphology evolution under different inclination angles were explored. Based on video analysis and OpenCV processing, the regulation of jet morphology and impact mode by the incidence angle was revealed. Combined with white light interferometry and ultra-depth-of-field three-dimensional microscopy, the ablation depth and material removal rate were quantitatively characterized. The results showed that under normal incidence, the maximum material removal rate of 0.092 mm³/s was achieved at 9 W, while further increases in power led to a decrease in removal rate due to bubble aggregation. When the sample was tilted to 15°, the material removal rate reached 0.163 mm³/s, representing a 106.30% improvement compared to that at 0°, and the ablation depth also peaked with an average maximum depth of 12.32 ± 0.58 μm and a single-point maximum of 54.36 μm. Furthermore, scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) were employed to elucidate the microstructural features and elemental distribution under different process parameters. Through multi-parameter experiments, this study achieved process parameter optimization and clarified the material removal mechanism influenced by different incidence angles, providing both a process reference and theoretical basis for efficient micro-machining of aerospace materials. Full article

Terrestrial Laser Scanning (TLS) can provide detailed three-dimensional structural information for individual trees and has become an important data source for tree species classification. However, most existing models are trained using leaf-on point clouds and therefore tend to rely heavily on leaf distribution and crown appearance. When the input changes from leaf-on point clouds to woody-dominated representations, classification performance often declines. To address this issue, this study proposes a mixed-input tree species classification framework for six typical temperate broadleaf tree species. First, a KPConv-based wood–leaf separation model was used to extract woody point sets from leaf-on TLS point clouds, thereby generating woody-only representations for subsequent classification. Second, a multi-task learning network based on DGCNN was constructed. In addition to the main task of tree species classification, an auxiliary task for input-representation discrimination was introduced to enhance the model’s adaptability to different input forms. Experiments were conducted using a dataset composed of local TLS samples from China and publicly available single-tree point clouds from the BioDiv dataset. The results show that the proposed method achieved an overall accuracy of 94.3% on the mixed test set of six typical broadleaf tree species, with average Precision, Recall, and F1 values of 94.3%, 93.6%, and 93.9%, respectively. These results indicate that integrating woody structural representations with multi-task learning can effectively alleviate overreliance on leaf-on appearance features and improve classification robustness under different input representations. Full article

The integration of vertical greenery systems (VGSs) into existing reinforced concrete (RC) buildings raises questions regarding interface kinematics and the permanent displacement of soil-retaining elements under seismic excitation. This study experimentally investigates the residual displacement of façade-mounted living walls and rooftop planter pods anchored to a deficient RC frame under shake table excitation. A 1:3 scale reinforced concrete frame was tested in two distinct phases: initially as a deficient, unretrofitted structure (Phase A), and subsequently as a retrofitted system integrated with vertical greenery elements (Phase B). High-precision terrestrial laser scanning (TLS) was employed before and after successive seismic excitation stages to generate dense three-dimensional point clouds. Cloud-to-cloud comparison techniques were used to quantify global structural displacement and local kinematic behavior of greenery components, while results were validated against conventional displacement sensors. The RC frame exhibited millimeter-scale permanent displacements consistent with draw-wire measurements. In contrast, planter pods demonstrated configuration-dependent behavior, including up to 8 cm translational sliding and rotational responses reaching 13° under repeated excitation, whereas living wall panels remained stable. Notably, a 95% reduction in point cloud density reproduced global deformation patterns with an RMSE of 3.03 mm and quantified peak displacements with only ~2% deviation from full-resolution results. The findings demonstrate the capability of TLS-based monitoring to detect differential kinematic behavior of integrated VGSs, while highlighting the variability in performance of friction-based rooftop anchorage utilizing different robust planter pod fixing systems. Full article

The methodical work describes all the necessary steps for establishing a stable oral ex vivo biofilm using saliva and crevicular plaque samples from periodontal healthy donors. First, cover slips were preconditioned with saliva supernatants and subsequently inoculated with crevicular plaque suspensions. Ex vivo biofilm formation was characterized by confocal laser scanning microscopy (cLSM) after 1, 4, 24, 48 and 72 h of anaerobic cultivation. Exemplarily, the inhibitory characteristics of blackcurrant fruit extracts [all-fruit juice (AFJ); alcoholic fraction from berry skins (AFBS)] were observed on 1, 4 and 24 h-aged ex vivo biofilms. Chlorhexidine (CHX, 0.2%) served as positive control. After direct contact (3 min), biofilms were dispersed, plated onto agar and anaerobically cultivated for 24 h. Early ex vivo biofilms (1 h-biofilm) showed scattered microbial colonies. After 4 h of cultivation, a multilayered biofilm was formed. Biofilm mass gradually increased, displaying a complex polymicrobial structure after 24 h. At 72 h, the biofilms had a dense three-dimensional appearance. Treatment with AFJ and CHX was more efficient in inhibiting biofilm growth compared to AFBS. Early biofilms (1 h, 4 h) were more susceptible to AFJ and CHX compared to 24 h-biofilms. The introduced model can be recommended for testing the efficiency of plaque-controlling agents. Full article

Laser powder bed fusion (LPBF) is susceptible to defects arising from melt pool instabilities, spatter, heat accumulation, and powder spreading anomalies. In situ infrared (IR) monitoring can detect these issues; however, it typically generates large volumes of data that are costly to store and analyze. This work proposes a projection-based framework that directly maps in situ thermal measurements onto a three-dimensional (3D) voxelized part geometry, substantially reducing storage requirements while preserving spatial fidelity. In addition, several IR derived features are incorporated into a practical workflow for defect detection and process model calibration, including laser scan order, local pre-deposition temperature, maximum pre-scan temperature, and spatter generation and landing locations. For completeness, commonly used metrics such as interpass temperature, heat intensity, cooling rate, and relative melt pool area are extracted within the same unified processing pipeline. All features are computed using a consistent, reproducible Python-based implementation to streamline integration into routine monitoring and analysis tasks. Multiple parts are fabricated, monitored, and characterized to evaluate the proposed framework, demonstrating that the extracted features reliably identify process anomalies and correlate with observed defects. Full article

The shift toward lightweight powertrain architectures necessitates a detailed characterization of polymer gears to verify their efficiency and durability. This study investigated the effectiveness of non-contact structured-light 3D scanning for evaluating the surface topography and dimensional tolerance quality of polymer gears produced via distinct manufacturing technologies. A structured-light 3D scanner was used to capture dense point clouds (exceeding 6 million points) of gears produced by three methods: conventional hobbing (POM-C), Material Extrusion (MEX) with carbon fiber reinforcement, and Selective Laser Sintering (SLS). The manufactured parts were compared against the nominal Computer Aided Design (CAD) models to evaluate their geometrical deviations in accordance with DIN 3961 and surface roughness parameters per ISO 25178. The experimental results revealed a consistent ranking of manufacturing quality. The conventionally hobbed POM-C gear exhibited superior precision, achieving DIN quality grades of Q9–Q10 and the smoothest surface finish (S_a = 5.0 µm). Among additive manufacturing techniques, SLS-printed PA 12 showed intermediate quality (Q11, S_a = 12 µm), whereas MEX-printed PPS-CF exhibited significant deviations (exceeding Q12) and the highest surface irregularity (S_a = 25 µm) due to stair-stepping effects. These findings indicate that while additive manufacturing offers geometric flexibility, conventional hobbing retains a decisive advantage in dimensional precision. The optical scanning methodology demonstrated here constitutes an efficient metrological framework for gear quality control, with potential applications extending to the quality assurance of additively manufactured adaptive fixtures and assembly tooling, including automotive assembly operations. Full article

Archaeological sites characterized by the coexistence of extensive above-ground terrain and hypogeum structures present major challenges for accurate and comprehensive geospatial documentation. Conventional survey approaches—such as static terrestrial laser scanning (TLS), total-station measurements, and aerial photogrammetry—often suffer from operational constraints, particularly in the presence of narrow underground spaces, low or absent illumination, harsh environmental conditions, and restrictions on UAV deployment. Additional complexity arises when both surface and subterranean elements must be consistently georeferenced to a common global reference system, especially where establishing a traditional topographic–geodetic control network is impractical. Within the framework of the EIMAWA Egyptian–Italian Mission conducted by the University of Milano since 2018, the Geomatics group of the University of Bologna designed and implemented a multi-scale multi-technique 3D documentation workflow, with a prominent role assumed by Simultaneous Localization and Mapping (SLAM) mobile laser scanning. The approach was supported by GNSS measurements providing centimetric accuracy. SLAM was employed to document both the surface necropolis and multiple hypogeal tombs, enabling rapid acquisition of dense three-dimensional data in environments where traditional techniques are limited. All datasets were integrated within a unified reference system, resulting in a coherent, multi-layered spatial dataset representing both landscape and underground spaces. The results demonstrate that SLAM can produce dense point clouds that document at few-centimetric level accuracy and continuously both above- and below-ground contexts. Quantitative analyses of the co-registration and mutual alignment of multiple SLAM datasets confirm a high degree of internal consistency, further enhanced through post-processing refinement. Overall, the experience indicates that this solution represents a practical and reliable technique for complex archaeological surveying. Full article

Deformation monitoring of roadway surrounding rock is the key link to ensure the safety production of the coal mine. The traditional monitoring method can only obtain the displacement information of discrete measuring points, and it is difficult to fully reflect the spatial distribution characteristics and evolution law of surrounding rock deformation. Based on the engineering background of the extra-thick coal seam roadway in the Yushupo Coal Mine, Shanxi Province, China, this study proposes a set of full-space deformation monitoring methods for roadway surrounding rock based on explosion-proof mobile 3D laser scanning technology. Firstly, a hierarchical denoising method based on improved statistical filtering is established. The quality of point cloud data is effectively improved by region clipping, a connectivity analysis guided by multi-dimensional geometric features and adaptive density threshold three-level processing strategy. Secondly, a hierarchical point cloud registration method combining physical anchor geometric constraints and deep learning patch guided matching is proposed to reduce the registration error to millimeter level. Finally, the deformation evaluation of surrounding rock is carried out by combining the overall deformation identification with the quantitative analysis of local section slices. The engineering application results show that the deformation of the roadway floor is the most significant during the monitoring period, the maximum deformation is 90.0 mm, and the average deformation is 46.9 mm. The maximum deformation of the roof is 35.0 mm, and the convergence of both sides is asymmetric. Compared with the total station, the results show that the maximum displacement error in each direction does not exceed 5 mm, and the standard deviation is within 1.3 mm, which meets the engineering accuracy requirements of coal mine roadway deformation monitoring. This study provides a complete technical scheme for panoramic and high-precision monitoring of surrounding rock deformation in coal mine roadway. Full article

Staphylococcus epidermidis is a leading opportunistic pathogen in medical device-associated infections due to its ability to adhere to abiotic materials and develop biofilms that are difficult to eradicate. This study investigated the antibiofilm potential of an ethanolic extract of the red seaweed Gracilaria fisheri and its purified constituent, N-benzylcinnamamide, against S. epidermidis. Antibacterial activity was determined, and antibiofilm effects were assessed using the crystal violet assay and confocal laser scanning microscopy (CLSM). Early bacterial adhesion on glass and polyurethane (PU) surfaces was measured. The effect on catheter-associated biofilms was evaluated by scanning electron microscopy (SEM). Transcripts of biofilm- and quorum-sensing-associated genes (icaA and luxS) were assessed by semi-quantitative RT-PCR. Cytotoxicity was evaluated by MTT assay. At 200 µg/mL, biofilm biomass decreased to 48.21 ± 5.52% with the extract and to 36.65 ± 6.82% with N-benzylcinnamamide. CLSM time-course imaging showed delayed biofilm maturation and less consolidated, discontinuous structures. Surface exposure to the extract markedly reduced early attachment on both materials. On PU catheter segments, SEM demonstrated that N-benzylcinnamamide markedly reduced surface coverage and disrupted three-dimensional biofilm architecture. At the molecular level, transcription of icaA and luxS was reduced. Both the extract and N-benzylcinnamamide showed minimal cytotoxicity in HeLa cells. These findings support further evaluation of these marine-derived agents as candidates for antibiofilm surface treatments to reduce early medical device colonization. Full article