Search Results (207)

Steel-framed modular structures, assembled by stacking modules, show distinct lateral behavior. However, the role of steel plate shear walls (SPSWs) in such structures is rarely studied. This study investigates their influence on the lateral behavior of steel-framed modular structures. Two six-story modular structures are designed: one without SPSWs while the other one with SPSWs. The base shear, failure process, and resisting mechanism of modular structures are studied by pushover analyses. Parametric studies address effects of plate thickness, bolt number, and cross-section of horizontal inter-module links. Contributions of SPSWs and concrete shear walls are compared. For the first time, three distinct resisting mechanisms—individual resisting unit, double-column system, and double-beam system—are identified and systematically explained in the context of SPSWs-enhanced modular structures. A novel tension-tie strip model is developed to quantify the contribution of SPSWs to lateral resistance. Results demonstrate that SPSWs work as tension-tie strips, significantly increasing the stiffness and resisting capacity of modular structures by three to five times depending on the loading direction. The resisting capacity grows with plate thickness. Insufficient bolts or link cross-section can lead to premature failure. Compared to concrete shear walls, SPSWs offer better integrity and drift control under extreme seismic loads. A design scheme is proposed to estimate the increased resistance due to SPSWs with good accuracy and efficiency, offering a practical tool for structural engineers to enhance lateral behavior. The findings provide new insights into the seismic design of modular buildings and establish a foundation for performance-based design of SPSW-reinforced modular structures. Full article

Utilising the open-source design of the Federica Prosthetic Hand, we introduce a redesigned print-in-place version that minimises assembly requirements without sacrificing functionality. The original Federica hand has a complicated, time-consuming assembly process. The print-in-place design removes the process of assembling the hand, making it easier for new users to use the design. The approach results in a 21% reduction in the bill of materials and a 21% reduction in weight. Though the 8 N force of the original Federica hand was not reached in this trial, the measured results show that under the same test conditions, the print-in-place hand can match the performance of the original. In a single-specimen analysis, the print-in-place hand produced a higher peak force in four of eight orientations. The redesigned prosthetic hand includes functional joints fully integrated into its structured design with a locking mechanism, eliminating the need for several metal bolts, and a revised dorsal finger contour, reducing the requirement for additional support structures during printing. As with the original hand, the print-in-place prosthetic is open source for anyone to access. Full article

Smart and sustainable construction increasingly depends on automation, yet robotic steel assembly still lacks task-specific perception data for bespoke connection systems. The Intermeshed Steel Connection (ISC) is a novel steel connection system that can reduce bolting effort and support faster, more reusable assembly, but dependable perception for ISC-aware robotic assembly remains underdeveloped. No public image corpus exists for ISC components, and collecting real site imagery is constrained by access, safety, privacy, and the limited deployment of ISC in practice. This paper introduces ISC-Perception, a hybrid vision dataset for near-field robotic assembly with novel Intermeshed Steel Connections. The dataset combines photorealistic CAD renders from SolidWorks Visualize, automatically annotated synthetic scenes generated in Unity, and a limited curated set of real ISC and human images. For a normalised 10,000-image Unity-based pipeline example, the proposed pipeline reduces estimated human effort to 30.5 h compared with 166.7 h for manual labelling, while the full training and validation set contains 15,928 images. Detectors trained on the hybrid dataset outperform synthetic-only and photorealistic-only alternatives, achieving mAP@0.50 of 0.756 on the complete test set. A near-size-matched comparison indicates that the improved performance is associated with the hybrid composition rather than dataset size alone under the evaluated training conditions. In a 1200-frame multi-view benchtop robotic assembly experiment, the detector achieves mAP@0.50/mAP@[0.50:0.95] of 0.943/0.823. These results show that ISC-Perception provides a practical route to data generation for emerging construction robotics applications where real imagery is scarce and supports the development of perception modules for robotic steel assembly in smart construction. Full article

Four full-scale exterior beam-to-column connections comprising H-section beams and square hollow-section (SHS) columns were tested under low-cycle reversed loading to investigate two engineering-oriented T-stub section configurations and the effects of the presence or absence of triangular stiffeners. Failure modes, moment–rotation response, stiffness degradation, energy dissipation, and cumulative damage were evaluated, together with nonlinear finite element simulations and a modified Park–Ang damage assessment. All specimens progressed from bolt-hole slip through plastic deformation to localized fracture. In the unstiffened connections, damage concentrated near the T-stub flange-to-web junction; stiffeners redistributed critical demand toward the stiffener welds, adjacent T-stub webs, and SHS column walls. The maximum differences in initial rotational stiffness relative to J1A were 15.69% and 15.07% in the positive and negative loading directions, indicating that the elastic-stage response reflected the combined deformability of the T-stub, blind-bolt assembly, and column wall. The maximum increases in yield moment, peak-resistance moment, and ductility coefficient were 20.59%, 43.71%, and 45.91%, respectively. Complete-history energy dissipation varied non-monotonically across the tested configurations. The finite element model reproduced the global and local responses, while the damage-index results showed overall correspondence with the observed failure progression. The findings emphasize stiffness compatibility and rational distribution of plastic demand rather than maximum local stiffness. Full article

As timber construction continues to expand toward taller and larger buildings, ensuring structural resilience under fire conditions requires advanced fire–structural performance assessment approaches. Such assessments generally integrate fire models to define thermal exposure, heat transfer models to predict temperature evolution within structural members, and structural models to evaluate fire-induced structural response. While substantial progress has been achieved in fire and thermal modelling, the structural modelling component, particularly constitutive representation of timber behaviour at elevated temperatures, remains comparatively less developed. This paper presents Wood^ST, a temperature-dependent plastic–damage constitutive modelling approach developed to advance the structural assessment of timber structures under fire conditions. The key modelling components of Wood^ST are briefly introduced, and its capabilities are demonstrated through applications to representative timber structural systems, including bending members (LVL, glulam w/o openings, OSB-web I-joists), axially loaded compression members considering stability effects, complex bolted timber connections and assemblies (light wood frame and hybrid timber–concrete floors) involving multiple interacting components and contact behaviour. The presented applications demonstrate the capability of Wood^ST to capture fire-induced material degradation, nonlinear response, instability, and structural interaction across multiple scales. These advances support performance-based fire design and contribute to the development and implementation of design codes and standards (e.g., CSA O86 and ISO TC92), while facilitating innovation in timber products and structural systems. Full article

This paper showcases the Aluminum Highway Bridge (AHB) project as a prime example of technical excellence, innovative thinking, and cross-disciplinary expertise in modern infrastructure. Supported by over 20 organizations from Canada, the U.S., and Europe, the AHB initiative pioneers low-carbon aluminum road bridges by integrating advanced design, fabrication, and welding technologies. The project’s rigorous approach to selecting aluminum extrusions, optimizing welded and bolted connections, and addressing logistical challenges demonstrates deep engineering insight. Emphasizing the material’s lightness, durability, and recyclability, the project aims to deliver compelling sustainability and life cycle benefits. Rooted in decades of research and strict adherence to modern engineering standards, the AHB methodology blends constructability with environmental responsibility. By developing a comprehensive framework and fostering collaboration across sectors, this initiative propels global aluminum bridge innovation. With about half of the project completed, this paper focuses on the materials procurement, the assembly options, the demonstration module fabrication and the environmental footprint. Full article

Non-contact metric inspection of metallic circular holes is essential for assembly quality control, yet remains difficult on reflective machined surfaces, where depth scale, stripe radiometry, and contour geometry degrade simultaneously. Pure monocular two-dimensional vision localizes hole boundaries efficiently but cannot resolve metric depth; multi-camera three-dimensional systems remove this ambiguity but with a heavier hardware and calibration cost; and conventional structured-light pipelines often improve stripe extraction or circle fitting in isolation, leaving the overall measurement chain fragile when reflection and edge defects co-occur. This paper proposes a monocular structured-light framework that treats sensing geometry, radiometric stripe reliability, and outlier-robust hole estimation as one coupled measurement chain. A single calibrated industrial camera is combined with an obliquely projected line laser to fuse top-view contour observation with light-plane-constrained depth recovery. Multi-exposure high-dynamic-range (HDR) fusion, adaptive Gaussian regularization, and distance-weighted gray-centroid refinement stabilize sub-pixel stripe centerlines under local saturation and uneven illumination, while geometry-aware contour screening and probabilistic multi-stage RANSAC fitting suppress burr-induced outliers during circle-parameter estimation. Experiments were conducted on a steel bolt-hole workpiece and a 6061 aluminum-alloy plate containing five holes with nominal diameters spanning approximately 30–78 mm. The original steel workpiece was evaluated for its diameter and two datum-related center-position quantities, while the five-hole plate was evaluated through three repeated optical diameter measurements and independent CMM references. For the five aluminum-alloy holes, the mean optical–CMM diameter differences ranged from 0.006 to 0.218 mm, with an average absolute difference of 0.096 mm. The results establish feasibility over the tested workpieces and calibrated measurement volume rather than generalization to arbitrary hole geometries, materials, or surface conditions. Full article

Predicting the mechanical properties of bolted connection nodes in prefabricated Concrete-Filled Steel Tube (CFST) column–steel beam assemblies remains challenging due to complex nonlinear relationships, high degrees of parameter coupling, and limited generalization capabilities of traditional empirical formulas. This study proposes a data-driven prediction model integrating an Improved Particle Swarm Optimization (IPSO) algorithm with a Deep Neural Network (DNN). Drawing upon 196 sets of experimental data on CFST column–steel beam nodes with Extended Hollo-Bolt (EHB) connections from the published literature, the model employs bolt diameter, steel tube wall thickness, concrete compressive strength, beam–column cross-sectional parameters, and connection configuration parameters as input variables, while designating ultimate moment capacity, initial stiffness, and joint ductility coefficient as prediction targets. A multi-layer DNN is constructed to capture the highly nonlinear mapping between structural parameters and mechanical responses. The IPSO algorithm, enhanced with adaptive inertia weight and Lévy flight perturbation, performs global optimization of the network weights and hyperparameters to improve convergence speed and prediction stability. Five-fold cross-validation is embedded within the IPSO fitness evaluation loop to guide hyperparameter selection, while dropout regularization and early stopping are applied during final training to mitigate overfitting; prediction performance is ultimately verified on an independent hold-out test set. Experimental results demonstrate that the proposed IPSO-DNN model outperforms a tuned shallow neural network (SNN), Support Vector Regression (SVR), and Random Forest (RF) models across the coefficient of determination ($R^2$), root mean square error (RMSE), and mean absolute error (MAE), effectively capturing the nonlinear mechanical characteristics of CFST nodes under complex loading conditions. Full article

The high-temperature sealing reliability of flange–bolt–gasket systems is governed by the coupled gasket leakage, flange cracking, and bolt yielding. This study investigates a DN200 PN40 (nominal diameter 200 mm and nominal pressure 4.0 MPa) weld-neck flange assembly operating under 300 °C superheated steam at 4 MPa internal pressure. Exploiting the assembly’s 12-fold cyclic rotational symmetry, a 1/12 periodic-sector finite element model with steady-state thermal–structural sequential coupling was developed in ANSYS Workbench and validated against the Omiya–Sawa 3-inch weld-neck flange benchmark at two levels (Level 1: bolt load vs. experiment; Level 2: 250 °C gasket contact pressure vs. reference finite element method (FEM)), with maximum errors below 1.5% in both levels; the benchmark thus establishes the reliability of the modeling procedure rather than constituting a direct experimental validation of the DN200 PN40 configuration. Using a central composite design, second-order response surface models (RSM) and Kriging surrogate models were constructed and compared, followed by Sobol global sensitivity analysis, multi-objective optimization using the non-dominated sorting genetic algorithm II (NSGA-II), and decision-making using the technique for order preference by similarity to ideal solution (TOPSIS), with bolt preload F and gasket width b as design variables. Baseline analysis revealed a differential contact pressure distribution—lower at the inner radius and higher at the outer radius—driven by a −0.308° flange rotation, identifying the inner gasket edge as the critical sealing failure path. RSM outperformed Kriging for the primary objective (mean absolute percentage error (MAPE): 0.72% vs. 3.61%), and the Pareto front collapsed to b = 19 mm. The TOPSIS-recommended optimum (F = 59,942 N, b = 19.00 mm), verified by ANSYS back-substitution, increased the minimum gasket contact pressure by 31.01% while reducing the flange membrane-plus-bending stress by 2.26%, achieving a coordinated improvement of both sealing performance and structural safety. Full article

To address the demand for lightweight commercial vehicle suspensions, this study investigates the replacement of traditional spring steel with E-glass fiber/epoxy composite materials. An equal-width, variable-thickness parabolic single-leaf spring was designed, with orthotropic mechanical properties obtained via ASTM standard tests. Finite element analysis (FEA) was combined with multi-objective optimization using a genetic algorithm, adjusting layup parameters to optimize stiffness, strength, and mass. Furthermore, to address the high failure risk at composite joints, a symmetric two-hole bolted end connection and a mid-span clamping structure were designed. The structural integrity was evaluated under vertical load, emergency braking, and steady-state cornering conditions using the Tsai–Wu tensor strength criterion. The optimization results demonstrate an 8.84% mass reduction for the composite spring main body compared to the initial design. The complete composite leaf spring assembly achieved approximately a 60.6% weight reduction relative to the original steel counterpart. The results indicate that the proposed design and optimization methodology effectively fulfills lightweighting objectives while satisfying all suspension performance and operational reliability requirements. Full article

Neutral salt spray tests were conducted on assemblies comprising H59 brass and either electrogalvanized or hot-dip galvanized bolts. The polarization curves, electrochemical impedance spectroscopy (EIS), corrosion morphology, elemental distribution, and corrosion product composition of the H59 brass were systematically characterized. The results demonstrated that upon coupling with galvanized bolts, the formation of a protective Cu₂O film on the H59 brass is significantly weakened, leading to accelerated corrosion. After coupling with electrogalvanized bolts, the i_corr reached a maximum value of 0.21 mA/cm². A corrosion layer predominantly composed of ZnO formed on the sample surface with a thickness of approximately 13 μm, and no penetration or enrichment of Cl was observed in the matrix. More seriously, when the brass was assembled with hot-dip galvanized bolts, the i_corr never dropped below 0.2 mA/cm². A porous and complex Zn-Cu-O-Cl mixed corrosion layer developed on its surface. This loose structure allows Cl⁻ to reach a depth of 55 μm into the matrix and continue causing corrosion. The mechanisms underlying the different corrosion behaviors of H59 brass caused by different galvanizing bolt processes require further investigation. Full article

Accurate detection and reliable grasping of small bolts are essential for intelligent manufacturing and automated assembly. However, this remains a challenge due to the small size, slender geometry, and metallic reflective surfaces of bolts. In this paper, we propose a vision-guided robotic bolt handling framework that integrates lightweight object detection, optimization-oriented grasp execution, and collision-aware trajectory planning. The lightweight YOLOv8n-BoltLite detector, improved with E-C2f, LCA, SA-PAN, and WD-IoU loss, enhances localization accuracy and feature representation for small and slender bolts. A robotic grasping framework is designed to transform detection results into executable robotic actions through 3D pose estimation, mid-shank grasp point generation, and optimization-oriented execution formulation. Additionally, a five-segment trajectory planning strategy ensures safe and efficient robot motion. Experimental results show that YOLOv8n-BoltLite achieves a five-run average mAP of 99.64 ± 0.05% with 198 FPS, and 3.02 M parameters. On an additional challenging external test set involving illumination variation, clutter, partial occlusion, reflection, and clustered bolts, the proposed detector achieves 94.62 ± 0.18%, outperforming recent lightweight detectors under the same training protocol. Robotic experiments involving 1000 controlled grasping trials and 300 multi-target grasping attempts demonstrate a controlled-condition success rate of 97.0% and improved target-selection reliability in multi-bolt scenes. These results suggest that the proposed framework offers a practical and efficient solution for automated bolt handling in intelligent manufacturing environments. Full article

To investigate the influence of dry connection methods on the seismic behavior of assembled composite walls, four assembled composite walls were designed and tested. Various dry connection techniques were adopted for the horizontal interfaces, namely sleeve grouting connection, welding connection, box connection, and bolted connection. The failure process, failure mode, bearing capacity, rigidity, steel bar strain, and energy absorption performance of the specimens were investigated through quasi-static cyclic loading tests. The results indicate that all types of connectors can effectively transfer loads and satisfy the conceptual design principle of “strong joint and weak component”. The damage evolution of the specimens is essentially identical, and the limiting drift angles all exceed 1/90. In addition, the shear resistance of the specimens with different connection methods is preliminarily analyzed and estimated. Full article

Conventional formwork systems are limited in their ability to efficiently realize complex and free-form concrete geometries, while additive manufacturing (AM)-based formwork faces constraints in casting-stage structural stability and cost-effectiveness, particularly at construction scale. To address these limitations, a hybrid formwork system integrating a structural steel frame with 3D-printed modules is proposed, in which the steel frame resists casting-induced lateral pressure while the printed components define complex mold geometries. The system was fabricated and validated through a full-scale case study structure measuring 3.0 m × 1.7 m × 2.2 m, produced using a large-scale fused deposition modeling (FDM) process with carbon-fiber-reinforced ABS (ABS-CF20). Geometric accuracy was evaluated by comparing design dimensions with as-built measurements across planar, edge, curved, and inclined regions. Construction efficiency and cost performance were assessed through process-based and cost-based comparisons with conventional steel formwork and fully 3D-printed formwork alternatives. The constructed structure reproduced the intended geometry with an average deviation of approximately 3.2 mm and a maximum deviation within ±4 mm, and no notable formwork deformation or damage was observed during concrete casting. Relative to conventional steel formwork, the hybrid system reduced total fabrication duration by about 50% and fabrication cost by about 60% based on a normalized cost index, while also outperforming fully 3D-printed formwork in cost efficiency by about 45%. The modular configuration and bolted connection system further improved transportability, on-site assembly efficiency, and component reusability. These findings demonstrate that the proposed hybrid formwork system provides a practical and resource-efficient pathway for fabricating complex concrete structures, supporting the broader adoption of digital fabrication in sustainable construction practice. Full article

To investigate the static behavior of UT-type assembled semi-rigid joints and the effects of bolt pretension loss, two representative joint configurations, UT250 × 150 and UT400 × 200, were studied by combining full-scale tests with refined finite element analysis using ABAQUS. Pure bending, bending-shear, and constant-axial-force-coupled loading conditions were considered, with particular attention paid to the effects of single-bolt and multiple-bolt pretension loss on moment capacity, initial rotational stiffness (K_y), interface slip, and the failure mode of the joints. The results show that the UT-type joint mainly fails through concentrated plastic yielding in the joint zone, and its ultimate moment (M_u) is 12.3–18.7% higher than that of a conventional bolted-welded joint, satisfying the design principle of “strong joint and weak member”. Loss of pretension in a single bolt has only a limited influence on the yield moment (M_y) and ultimate moment (M_u), with a maximum reduction of 8.0% in the ultimate moment (M_u) under negative pure bending; however, it causes clear degradation in the initial rotational stiffness (K_y), and pretension loss in the upper bolt produces a greater stiffness reduction than loss in a single lower bolt, with a maximum reduction of 33.43%. Multiple-bolt pretension loss exhibits a pronounced coupling effect. Simultaneous loss in lower bolts on the same side is the most unfavorable case, leading to a maximum stiffness reduction of 67.78% (coupling coefficient of 1.17), whereas diagonal loss is relatively controllable and generally keeps the stiffness reduction within 7%. When the axial compression ratio does not exceed 0.3, the mechanical response of the joint remains relatively stable, and the adverse effect of pretension loss can be alleviated to a certain extent; further increases in the axial compression ratio accelerate the degradation of both stiffness and load-carrying capacity. The present study provides a useful reference for the design optimization, construction quality control, and in-service maintenance of UT-type semi-rigid joints. Full article