Search Results (86)

Aging railroad bridges present complex challenges due to advancing deterioration and outdated design assumptions. This study develops a comprehensive analytical approach for assessing an aging steel truss railroad bridge through finite element (FE) modeling, sensitivity analysis, and model updating, supported by field testing. An initial FE model of the bridge was created based on original drawings and field observations. Field testing using a laser Doppler vibrometer captured the bridge’s dynamic response (vibrations and deflections) under regular train traffic. Key structural parameters (material properties, section properties, support conditions) were identified and varied in a sensitivity analysis to determine their influence on model outputs. A hybrid sensitivity analysis combining log-normal sampling and a genetic algorithm (GA) was employed to explore the parameter space and calibrate the model. The GA optimization tuned the FE model parameters to minimize discrepancies between simulated results and field measurements, focusing on vertical deflections and natural frequencies. The updated FE model showed significantly improved agreement with observed behavior; for example, vertical deflections under a representative train were matched within a few percent, and natural frequencies were accurately reproduced. This validated model provides a more reliable tool for predicting structural performance and fatigue life under various loading scenarios. The results demonstrate that integrating field data, sensitivity analysis, and model updating can greatly enhance the accuracy of structural assessments for aging railroad bridges, supporting more informed maintenance and management decisions. Full article

Masonry industrial buildings, common in the 19th and 20th centuries, represent a significant architectural typology. These structures are crucial to the study of industrial archeology, which focuses on preserving and revitalizing historical industrial heritage. Often left neglected and deteriorating, they hold great potential for adaptive reuse, transforming into vibrant cultural, commercial, or residential spaces through well-planned restoration and consolidation efforts. This paper explores a case study of such industrial architecture: a decommissioned factory near Naples. The complex consists of multiple structures with vertical supports made of yellow tuff stone and roofs framed by wooden trusses. To improve the building’s seismic resilience, a comprehensive analysis was conducted, encompassing its historical, geometric, and structural characteristics. Using advanced computer software, the factory was modelled with a macro-element approach, allowing for a detailed assessment of its seismic vulnerability. This approach facilitated both a global analysis of the building’s overall behaviour and the identification of potential local collapse mechanisms. Non-linear analyses revealed a critical lack of seismic safety, particularly in the Y direction, with significant out-of-plane collapse risk due to weak connections among walls. Based on these findings, a restoration and consolidation plan was developed to enhance the structural integrity of the building and to ensure its long-term safety and functionality. This plan incorporated metal tie rods, masonry strengthening through injections, and roof reconstruction. The proposed interventions not only address immediate seismic risks but also contribute to the broader goal of preserving this industrial architectural heritage. This study introduces a novel multidisciplinary methodology—integrating seismic analysis, traditional retrofit techniques, and sustainable reuse—specifically tailored to the rarely addressed typology of masonry industrial structures. By transforming the factory into a functional urban space, the project presents a replicable model for preserving industrial heritage within contemporary cityscapes. Full article

In this study, the human-induced vibration performance of an innovative Deltabeam–CLT composite floor system was investigated. The Deltabeam–CLT composite floors were modelled using the finite element software package ABAQUS 6.14, the dynamic performance of the composite floors was evaluated, and the simulation results were benchmarked against prior simulation data in the other literature. In order to investigate the effect of the stiffness of Deltabeam composite steel beams on the vibration performance of Deltabeam–CLT composite floors, the acceleration of the Deltabeam–CLT composite floors under the excitation of a single person walking was measured. As per the acceleration, serviceability factors, namely, response factors (RFs) and vibration dose values (VDVs), were analyzed. The results showed that an increase in the height of Deltabeam composite steel beams can decrease the RF and VDV by 53.7% and 57.7%, respectively. This study also developed an optimization scheme with steel trusses pre-embedded inside Deltabeam composite steel beams. The effects of different truss spacing and rod diameters on the vibration performance of the Deltabeam–CLT composite floors were investigated; the results showed that the RF and VDV of Deltabeam–CLT composite floors can decrease to below 4 and 0.4 m/s^−1.75, respectively, with a truss spacing smaller than 200 mm. These findings can significantly enhance the future design of the Deltabeam–CLT composite floor system, improving its serviceability and ensuring better performance in practical applications. Full article

This study proposes an Index-Based Neural Network (IBNN) framework for the static analysis of truss structures, employing a Lagrangian dual optimization technique grounded in the force method. A truss is a discrete structural system composed of linear members connected to nodes. Despite their geometric simplicity, analysis of large-scale truss systems requires significant computational resources. The proposed model simplifies the input structure and enhances the scalability of the model using member and node indices as inputs instead of spatial coordinates. The IBNN framework approximates member forces and nodal displacements using separate neural networks and incorporates structural equations derived from the force method as mechanics-informed constraints within the loss function. Training was conducted using the Augmented Lagrangian Method (ALM), which improves the convergence stability and learning efficiency through a combination of penalty terms and Lagrange multipliers. The efficiency and accuracy of the framework were numerically validated using various examples, including spatial trusses, square grid-type space frames, lattice domes, and domes exhibiting radial flow characteristics. Multi-index mapping and domain decomposition techniques contribute to enhanced analysis performance, yielding superior prediction accuracy and numerical stability compared to conventional methods. Furthermore, by reflecting the structured and discrete nature of structural problems, the proposed framework demonstrates high potential for integration with next-generation neural network models such as Quantum Neural Networks (QNNs). Full article

In this study, a brand-new algorithm called the Comprehensive Adaptive Enterprise Development Optimizer (CAED) is proposed to overcome the drawbacks of the Enterprise Development (ED) algorithm in complex optimization tasks. In particular, it aims to tackle the problems of slow convergence and low precision. To enhance the algorithm’s ability to break free from local optima, a lens imaging reverse learning approach is incorporated. This approach creates reverse solutions by utilizing the concepts of optical imaging. As a result, it expands the search range and boosts the probability of finding superior solutions beyond local optima. Moreover, an environmental sensitivity-driven adaptive inertial weight approach is developed. This approach dynamically modifies the equilibrium between global exploration, which enables the algorithm to search for new promising areas in the solution space, and local development, which is centered on refining the solutions close to the currently best-found areas. To evaluate the efficacy of the CAED, 23 benchmark functions from CEC2005 are chosen for testing. The performance of the CAED is contrasted with that of nine other algorithms, such as the Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), and the Antlion Optimizer (AOA). Experimental findings show that for unimodal functions, the standard deviation of the CAED is almost 0, which reflects its high accuracy and stability. In the case of multimodal functions, the optimal value obtained by the CAED is notably better than those of other algorithms, further emphasizing its outstanding performance. The CAED algorithm is also applied to engineering optimization challenges, like the design of cantilever beams and three-bar trusses. For the cantilever beam problem, the optimal solution achieved by the CAED is 13.3925, with a standard deviation of merely 0.0098. For the three-bar truss problem, the optimal solution is 259.805047, and the standard deviation is an extremely small 1.11 × 10⁻⁷. These results are much better than those achieved by the traditional ED algorithm and the other comparative algorithms. Overall, through the coordinated implementation of multiple optimization strategies, the CAED algorithm exhibits high precision, strong robustness, and rapid convergence when searching in complex solution spaces. As such, it offers an efficient approach for solving various engineering optimization problems. Full article

Strategically important objects, such as dams, tunnels, bridges, and others, require long-term structural health monitoring programs in order to preserve their structural integrity with minimal downtime, financial expenses, and increased safety for civilians. The current study focuses on developing a damage detection methodology that is applicable to the long-term monitoring of such structures. It is based on the identification of resonant frequencies from operational modal analysis, removing the effect of environmental factors on the resonant frequencies through support vector regression with optimized hyperparameters and, finally, classifying the global structural state as either healthy or damaged, utilizing the Mahalanobis distance. The novelty lies in two additional steps that supplement this procedure, namely, the nonlinear estimation of the relative effects of various environmental factors, such as temperature, humidity, and ambient loads on the resonant frequencies, and the selection of the most informative resonant frequency features using a non-parametric neighborhood component analysis algorithm. This methodology is validated on a wooden two-story truss structure with different artificial structural modifications that simulate damage in a non-destructive manner. It is found that, firstly, out of all environmental factors, temperature has a dominating decreasing effect on resonance frequencies, followed by humidity, wind speed, and precipitation. Secondly, the selection of only a handful of the most informative resonance frequency features not only reduces the feature space, but also increases the classification performance, albeit with a trade-off between false alarms and missed damage detection. The proposed approach effectively minimizes false alarms and ensures consistent damage detection under varying environmental conditions, offering tangible benefits for long-term SHM applications. Full article

The deformation monitoring of integrated truss structures (ITSs) is essential for ensuring the reliable performance of mounted equipment in complex space environments. Reconstruction methods based on local strain information have been proven effective, yet the identification faces significant challenges due to variable thermal–mechanical loads, interactions among structural components, and special boundary conditions. This paper proposes a deformation reconstruction strategy tailored for ITSs under combined thermal–mechanical load scenarios wherein deformations of both the primary truss structures and the attached panel systems are investigated. The proposed approach utilizes Ko displacement theory as the core algorithm, while the least squares optimization method is employed to determine the integration with unknown initial values during the reconstruction process. Validation is conducted through diverse load scenarios, and the reconstruction results are evaluated using errors based on the root mean square. The result demonstrates that the proposed method can reconstruct deformations of truss structures under both mechanical and thermal loads. Furthermore, the optimization-based approach achieves accurate reconstructed results in the case of panels with two-point fixed boundary conditions. This study provides an effective strategy for in-orbit deformation reconstruction, addressing challenges posed by complex loads and structural configurations. Full article

In order to avoid the instability of compression support in annular space cable truss structures, a novel full-tension crossed cable-truss structure (FCCTS) is studied. Firstly, according to the geometric shape of cables, the distribution law of cable force in the pre-stressed state is deduced and analyzed by theory. According to the characteristics of the cable force of vertical cables being much smaller than that of upper and lower chord cables, a forming method of tensioning vertical cables, namely, the vertical cable-shortening method (VSM), is proposed. Corresponding node connection devices are also designed and tested. Subsequently, the VSM process for establishing tension is elaborated in detail, and its feasibility is numerically simulated and validated. The results clearly show that VSM can effectively establish the pre-stress state in FCCTS. The VSM has the advantage of low applied tension, making it easier to form structural tension. Full article

Surrogate-assisted evolutionary algorithms (SAEAs) are widely used in the field of high-dimensional expensive optimization. However, real-world problems are usually complex and characterized by a variety of features. Therefore, it is very challenging to choose the most appropriate surrogate. It has been shown that multiple surrogates can characterize the fitness landscape more accurately than a single surrogate. In this work, a multi-surrogate-assisted multi-tasking optimization algorithm (MSAMT) is proposed that solves high-dimensional problems by simultaneously optimizing multiple surrogates as related tasks using the generalized multi-factorial evolutionary algorithm. In the MSAMT, all exactly evaluated samples are initially grouped to form a collection of clusters. Subsequently, the search space can be divided into several areas based on the clusters, and surrogates are constructed in each region that are capable of completely describing the entire fitness landscape as a way to improve the exploration capability of the algorithm. Near the current optimal solution, a novel ensemble surrogate is adopted to achieve local search in speeding up the convergence process. In the framework of a multi-tasking optimization algorithm, several surrogates are optimized simultaneously as related tasks. As a result, several optimal solutions spread throughout disjoint regions can be found for real function evaluation. Fourteen 10- to 100-dimensional test functions and a spatial truss design problem were used to compare the proposed approach with several recently proposed SAEAs. The results show that the proposed MSAMT performs better than the comparison algorithms in most test functions and real engineering problems. Full article

Firstly, in this study, we utilize the high-order element model (truss link model) simulation method in OpenSees (3.7.0) software and verify the feasibility of this method by comparing it with the shaking table test. Secondly, the structural dynamic response of adjacent structures with different performance levels, spacing, and layout forms under large earthquakes is analyzed, and the corresponding structural failure probability is studied. Furthermore, the life distribution within the design service life of the structure is predicted according to the nonparametric Kaplan–Meier estimation model. Finally, the reliability of adjacent structures is evaluated by using the joint engineering demand parameters. The analysis method of replacing the theoretical analysis based on engineering experience and certainty in the current specification with probability analysis is proposed, which provides a more reliable theoretical basis for decision-making regarding the reinforcement, maintenance, or demolition of structures in the later stage. Full article

The proposed method involves the utilization of a strip roll-forming technique to fulfill the specific requirements for constructing large-scale structures in orbit and space station trusses during extraterrestrial exploration. This involves progressively rolling out a metal strip with an L+V-shaped locking edge through multiple passes of forming rolls featuring different section shapes. The process of helical locking enables the formation of a slender, spiral-shaped tube, which can be utilized for the in-orbit assembly of exceptionally large structures. The proposed approach introduces a two-step optimization method to enhance the maximum stress, equivalent plastic strain, and wrapping torque of roll-forming L+V cross-sections and wrap-forming helical tubes. The optimized sample points in the second step are established based on the optimal roll distance and roll gap obtained in the first optimal step, resulting in the determination of the optimal folding height and V-shaped angle of the L+V strip cross-section after optimization. The design of the strip wrapping configuration that follows is highly dependent on these four parameters. Full article

This paper presents a virtual dynamic vibration absorber (DVA) trap fusion active vibration suppression algorithm based on inertial actuators as a solution to the harmonic vibration control problem of large flexible space trusses. Firstly, the mechanism of the inertial actuator is analyzed, and the relationship between the bandwidth of the algorithm and the intrinsic frequency of the inertial actuator is derived. Secondly, a dynamic model of the space truss is constructed. Subsequently, an analysis is conducted to determine the manner in which the virtual DVA exerts influence on the system’s dynamic characteristics. Based on this analysis, a virtual DVA trap fusion active vibration suppression algorithm is designed. Finally, the efficacy of the proposed algorithm in suppressing vibration is demonstrated through experimentation. The algorithm was demonstrated to be effective in suppressing both single-frequency harmonic vibration and multi-frequency harmonic vibration under the working conditions of single-degree-of-freedom and multi-degree-of-freedom of a flexible truss. The vibration suppression efficiency was found to be greater than 60%. It is therefore evident that the proposed algorithm has the potential to be applied to the vibration suppression of telescopes assembled in orbit in the future. Full article

This article aims to address the in-orbit assembly needs of truss structures in space missions by designing a robot capable of moving on trusses and manipulating parts. To enhance the stability of the robot during movement and part manipulation, inspiration was drawn from the Dynastes Hercules beetle. Building upon detailed research on the Dynastes Hercules beetle, a biomimetic structure was designed for the robot system. Based on specific task requirements, the overall plan of the robot was developed, and its kinematic and dynamic models were derived. A prototype of the robot was created, which is capable of both movement and assembly functions, including handling spherical and rod-like objects. Through a series of experiments conducted with the robot, the research results demonstrated that the proposed design can effectively achieve the intended functions. Full article

Inspired by classical experiments that uncovered the inherent properties of light waves, Young’s Double-Slit Experiment (YDSE) optimization algorithm represents a physics-driven meta-heuristic method. Its unique search mechanism and scalability have attracted much attention. However, when facing complex or high-dimensional problems, the YDSE optimizer, although striking a good balance between global and local searches, does not converge as fast as it should and is prone to fall into local optimums, thus limiting its application scope. A fractional-order boosted hybrid YDSE, called FYDSE, is proposed in this article. FYDSE employs a multi-strategy mechanism to jointly address the YDSE problems and enhance its ability to solve complex problems. First, a fractional-order strategy is introduced into the dark edge position update of FYDSE to ensure more efficient use of the search potential of a single neighborhood space while reducing the possibility of trapping in a local best. Second, piecewise chaotic mapping is constructed at the initial stage of the population to obtain better-distributed initial solutions and increase the convergence rate to the optimal position. Moreover, the low exploration space is extended by using a dynamic opposition strategy, which improves the probability of acquisition of a globally optimal solution. Finally, by introducing the vertical operator, FYDSE can better balance global exploration and local exploitation and explore new unknown areas. The numerical results show that FYDSE outperforms YDSE in 11 (91.6%) of cec2022 sets. In addition, FYDSE performs best in 8 (66.6%) among all algorithms. Compared with the 11 methods, FYDSE obtains the optimal best and average weights for the 20-bar, 24-bar, and 72-bar truss problems, which proves its efficient optimization capability for difficult optimization cases. Full article

A servicing spacecraft motion control approach for the problem of on-orbit truss structure assembly is developed in this paper. It is considered that a cargo container with a rod set and servicing spacecraft are in orbit initially. The assembly procedure is based on spacecraft free-flight motion between the structure’s specified points. The spacecraft is equipped with two robotic manipulators capable of attaching to the structure and holding rods. In addition, the spacecraft can repulse from the structure with a given relative velocity using a manipulator, so the spacecraft and the structure receive impulses. The repulsion velocity vector is calculated in order to reach the structure target point to deliver and install the rod into the truss structure, or to reach the cargo container and take a rod. The problem of searching the repulsion velocity is formulated as an optimization problem with constraints, taking into account the limited value of the repulsion velocity, collision avoidance with structure, restrictions on the angular velocity and translational motion of the structure in the orbital reference frame. This problem is solved numerically with an initial guess vector obtained analytically for simplified motion cases. The application of the proposed control scheme to the assembly of a truss-based antenna is demonstrated. It is shown that the servicing spacecraft is successfully transferred between the structure points by means of manipulator repulsion. Main features and limitations of the assembly problem using a spacecraft with two manipulators are discussed. Full article