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In working processes, mechanical systems are often affected by both internal and external forces, which are the cause of the forced vibrations of the structures. They can be destroyed if the amplitude of vibration reaches a high enough value. One of the most popular ways to reduce these forced vibrations is to attach tuned mass damper (TMD) devices, which are commonly added at the maximum displacement point of the structures. This paper presents the computed results of the free vibration and the vibration response of the space frame system under an external random load, which is described as a stationary process with white noise. Static and dynamic equations are formed through the finite element method. In addition, this work also establishes artificial neural networks (ANNs) in order to predict the vibration response of the first frequencies of the structure. Numerical studies show that the data set of the TMD device strongly affects the first frequencies of the mechanical system, and the proposed artificial intelligence (AI) model can predict exactly the vibration response of the first frequencies of the structure. For the forced vibration problem, we can find optimal parameters of the TMD device and thus obtain minimum displacements of the structure. The results of this work can be used as a reference when applying this type of structure to TMD devices.

The effect of soil-structure interaction on the optimum design of steel space frames is investigated using metaheuristic algorithms. Three-parameter elastic foundation model is used to incorporate soil-structure interaction. A computer program is developed in MATLAB interacting with SAP2000-OAPI for two way data flow in all optimization procedures. Optimum design of space frames is formulated according to LRFD-AISC (Load and Resistance Factor Design, American Institute of Steel Construction) specifications. The parameters of foundation model are obtained by using soil surface displacements. It is concluded that consideration of soil-structure interaction ends up with heavier frames, and method is applicable for practical purposes.

Space frame structures that are made up of a huge number of members are often used on a large scale, hence their accurate evaluation is important to achieve the optimal design. On the other hand, the use of space Frames and 3D truss structures has become more popular due to its time efficiency. Also, these types of structures can carry loads in longspan buildings and are used in large-scale structures such as halls, hangars, passenger stations, etc. In this study, a novel evolutionary algorithm, named ETLBO, has been proposed for the optimization of space frame design in real-size structures. Despite the existing methods in the literature, the ETLBO method can be used for large-scale space frame structures due to its high speed with sufficient accuracy. At first, four optimization algorithms Particle swarm optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Teaching–learning-based optimization (TLBO) under structural problems have been evaluated. The results show that the TLBO algorithm performs better in solving problems and has been better in most problems than other algorithms. So, we have tried to improve this algorithm based on a machine learning approach and combination operators. Algorithm improvement is created by adding a crossover operation between the new solution and the best solution in the teacher phase. This change causes a sudden movement and escapes from the local minima for the algorithm. Enhanced algorithm results show that convergence speed and optimal response quality have improved. Finally, using this algorithm, several new practical examples have been optimized.

As-built building information modeling (BIM) model has gained more attention due to its increasing applications in construction, operation, and maintenance. Although methods for generating the as-built BIM model from laser scanning data have been proposed, few studies were focused on full-scale structures. To address this issue, this study proposes a semi-automated and effective approach to generate the as-built BIM model for a full-scale space frame structure with terrestrial laser scanning data, including the large-scale point cloud data (PCD) registration, large-scale PCD segmentation, and geometric parameters estimation. In particular, an effective coarse-to-fine data registration method was developed based on sphere targets and the oriented bounding box. Then, a novel method for extracting the sphere targets from full-scale structures was proposed based on the voxelization algorithm and random sample consensus (RANSAC) algorithm. Next, an efficient method for extracting cylindrical components was presented based on the detected sphere targets. The proposed approach is shown to be effective and reliable through the application of actual space frame structures.

In this article, two algorithms are presented for the optimum design of geometrically nonlinear steel space frames that are based on simulated annealing and genetic algorithm. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as the American Institute of Steel Construction (AISC) wide-flange shapes. Stress constraints of AISC Load and Resistance Factor Design (LRFD) and AISC Allowable Stress Design (ASD) specifications, maximum (lateral displacement) and interstorey drift constraints, and also size constraints for columns were imposed on frames. The algorithms were applied to the optimum design of three space frame structures, which have a very small amount of nonlinearity. The unconstrained form of objective function was applied in both optimum design algorithms, and constant penalty factors were used instead of gradually increasing ones. Although genetic algorithm took much less time to converge, the comparisons showed that the simulated annealing algorithm yielded better designs together with AISC-LRFD code specification.

Controlling the surrounding rock of the main roadway passing through a goaf during the reconstruction and expansion of a merger and reorganization mine is a common challenge in underground mining practices. In this study, a combined support technology of roof “anchorage‐mesh‐shotcrete” and a double‐H‐type space frame structure for a main roadway passing through a goaf was studied using field investigations, theoretical analysis, and engineering practice. It was observed that the main roadway control difficulties lie in the strongly mining‐induced roof strata in the early stages, with collapsed gangues not connected to an unsupported roof, large goaf sections, and multiple superpositions of surrounding rock stress fields with complex distributions. Based on the results, a double‐H‐type space frame structure support system comprising a “reinforced concrete pillar + reinforced concrete longitudinal beam + cross steel I‐beam” was constructed. This provided strong pillar support, enhanced the shock resistance of the roof, improved the bending and lateral pressure resistances of the frame structure, and produced airtight spaces for the main roadway. Accordingly, a “double systems” support scheme was designed. The results of the engineering practice indicated that the deformation of the goaf roof and force of the supporting structure were controlled within a safe range, meeting the requirements for mine ventilation, pedestrians, and haulage. Consequently, the surrounding rock control problem for the main roadway passing through the goaf was effectively solved, and theoretical and technical bases were provided for the stability control of a roadway passing through a goaf under similar conditions. A “double systems” support technology for the main roadway passing through the goaf is proposed. A high‐strength “anchorage‐mesh‐shotcrete” support system is adopted to form a large‐scale overall anchorage bearing structure for the goaf roof, and a double‐H‐type space frame structure support system of “reinforced concrete pillar + reinforced concrete longitudinal beam + cross steel I‐beam” is adopted to support the roof and construct the airtight spaces for the main roadway. This combined support technology provides the safety guarantee of the main roadway passing through the goaf.

In this paper, an optimization process using MATLAB-SAP2000 Open Application Programming Interface (OAPI) is presented for optimum design of space frames with semi-rigid connections. A specified list including W-profiles taken from American Institute of Steel Construction (AISC) is used in the selection of suitable sections. The stress constraints as indicated in load and resistance factor design of AISC, lateral displacement constraints being the top- and inter-storey drift and geometric constraints are considered in the optimization process. Genetic algorithm method based on biological principles and harmony search algorithm method based on the processes of musical harmony are used for optimum designs. Two different space frames are solved for the cases of rigid and semi-rigid connections, separately. A computer program is coded in MATLAB for the purpose interacting with SAP2000 OAPI. Results obtained from the analyses show that type of semi-rigid connections plays a crucial role in the optimization of steel space frames and increases the optimum weight.

This study investigates the dynamic performance of a large-span suspended steel space frame-glass composite floor (SSSF-GCF). Both the ambient vibration and the human-induced vibration of the floor were experimentally measured to identify vertical dynamic characteristics and evaluate vibration serviceability of the floor. Although vertical dynamic characteristics of the floor based on the global simplified finite element (FE) model of the structure agree well with those identified via experimental modal analysis, the global simplified FE model significantly underestimates vertical vibration amplitudes of the floor due to the coupled effect between two layers. Accordingly, an equivalent local FE model of the floor system was proposed and updated via adjusting the vertical stiffness of the interstory hanging pillars. It is shown that the equivalent local FE model can well predict both the dynamic characteristics and human-induced vibration response of the floor. Finally, the effect of the damping ratio on the acceleration response of the floor was numerically demonstrated with the verified local FE model.

A distributed remote collaborative hybrid test (RCHT) method for complex substructures based on OpenFresco is presented in this paper. Challenges in the RCHT include the modeling of the numerical substructure, boundary degree-of-freedom (DOF) loading, and equivalent communication of the multi-story space frame as a test substructure in OpenFresco. The effectiveness and accuracy of the proposed RCHT method are verified by a series of remote distributed tests that reproduce the seismic response of a three-story five-span space Y-shaped eccentric brace steel frame model consisting of two test substructures and a numerical substructure. The main contributions of this study are the realization of the multi DOF loading RCHT of the space global frame and reasonable simplification of the substructure boundaries, which further promotes the use of the RCHT method to realize the seismic performance simulation of complex substructures.