Large-scale Building Structures Research Articles

К вопросу о развитии методов измерения вибрации строительных конструкций

Vibration processes contain useful information about the properties of both the signal source and the medium in which they propagate. Control of vibration parameters of structures is an integral part of monitoring. There are various methods and means of measuring vibration processes in building structures, as well as their registration. The development of technology and electronics allows us to steadily improve the parameters of vibration sensors, reduce their dimensions and create fundamentally new sensitive elements. Examples are given of vibration measuring equipment used by the staff of the Institute of Continuous Media Mechanics for testing large-scale building structures over the past 25 years. The results of vibration measurements of large-scale structures are shown, as well as the evolution of the natural frequency of a building structure during its long-term monitoring.

Intelligent Assessment Method of Structural Reliability Driven by Carrying Capacity Sustainable Target: Taking Bearing Capacity as Criterion

Large-scale building structures are subject to numerous uncertain loads during their service life, leading to a decrease in structural reliability. Real-time analysis and accurate prediction of structural reliability is a key step to improve the bearing capacity of buildings. This study proposes an intelligent assessment method for structural reliability driven by a sustainability target, which incorporated digital twin technology to establish an intelligent evaluation framework for structural reliability. Under the guidance of the evaluation framework, the establishment method of a structural high-fidelity twin model is formed. The mechanical properties and reliability analysis mechanism are established based on the high-fidelity twin model. The theoretical method was validated by experimental analysis of a rigid cable truss construction. The results showed the simulation accuracy of the high-fidelity twin model formed by the modeling method is up to 95%. With the guidance of the proposed evaluation method, the mechanical response of the structure under different load cases was accurately analyzed, and the coupling relationship between component failure and reliability indicators was obtained. The twinning model can be used to analyze the reliability of the structure in real time and help to set maintenance measures of structural safety. By analyzing the bearing capacity and reliability index of the structure, the safety of the structure under load is guaranteed. The sustainability of structural performance is achieved during the normal service period of the structure. The proposed reliability assessment method provides a new approach to improving the sustainability of building bearing capacity.

AN RBF BASED HIGH-DIMENSIONAL MODEL REDUCTION APPROACH IN BUILDING OPTIMIZATION

Building optimization has gained importance with the recent push to create the most economical and efficient buildings possible. As the effects of optimization are a function of the building size, it is crucial to understand and further develop optimization techniques for large-scale building structures. Practical structural optimization of buildings requires the use of a structural analysis software package and an iterative optimization procedure. As a result, finite element (FE) software shall be linked with an optimization solver. It is an expensive process which requires extensive computer coding. Alternative methods are available, including metamodeling methods, which are used to create simple and approximate functions based on complex FE simulations. In this study, the approximate functions are generated using a high-dimensional model representation (HDMR) framework. The HDMR framework is a model reduction approach and is found to be very accurate for different functions. The component functions of HDMR are expressed using augmented radial basis functions (RBFs). To further improve the numerical efficiency of the metamodels and reduce the total required number of structural analyses, a few different HDMR sampling approaches are investigated, including one static approach and two iterative strategies. An existing nonlinear programming (NLP) solver is employed in the design process. To illustrate the proposed approach, a three-dimensional building structure is selected as a numerical example. The numerical optimization is conducted to reduce the torsional response of the building. The proposed optimization method works very well and the results from different HDMR techniques are compared.

Experimental and Theoretical Studies of Bidirectional Variable Curvature Friction Pendulum Bearing

In this study, to satisfy the base isolation demand of large-scale building structures under different earthquake records, a new bidirectional variable curvature friction pendulum bearing (BD-VCFPB) is proposed. The VCFPB is designed in detail based on the basic principle of a friction pendulum system. Moreover, the sliding interface function, gap between the slider and the sliding interface, and polytetrafluoroethylene (PTFE) plate stress are studied. Finally, a dynamic cyclic test is conducted to study the influence of the slider size, contact pressure on the PTFE plate, and loading frequency on the hysteretic behavior of the VCFPB. The results indicate that the hysteretic curves of the horizontal force and the displacement are regular, symmetrical, stable, and full, and clearly reflect the variable curvature convex and concave characteristics and the excellent behavior of energy dissipation of the BD-VCFPB. The sliding friction coefficient varies significantly with the contact pressure on the PTFE plate and the loading frequency; however, it has little relation with the slider size. A hysteretic model is proposed based on the results of a unidirectional test, and it is in good agreement with the hysteretic curves of the horizontal force and the displacement from a bidirectional test.

Research on the optimisation of complex models of large-scale building structures dependent on adaptive grey genetic algorithms

Genetic algorithm (GA) is a bionics algorithm based on the biological evolution theory that has received extensive attention in the field of computer science and optimisation in recent years. This paper analyses and integrates the relevant contents of genetic algorithm and its application in the optimal design of large-scale building structures and analyses and researches briefly several key factors when the genetic algorithm is applied to the optimal design of large-scale building structures, such as mathematical modelling, constraint condition treatment, generation of initial population and selection of control parameters of genetic algorithm. However, because the simple genetic algorithm is only good at global search, and the local search ability is not enough, it will take quite a long time to achieve the real optimal solution. For the shortcomings of simple genetic algorithm, an improved adaptive grey genetic algorithm is proposed in this paper. The example shows that the obtained adaptive genetic algorithm can improve the convergence and calculation speed when the genetic algorithms is applied to structural optimisation design.

Research on the optimisation of complex models of large-scale building structures dependent on adaptive grey genetic algorithms

Genetic algorithm (GA) is a bionics algorithm based on the biological evolution theory that has received extensive attention in the field of computer science and optimisation in recent years. This paper analyses and integrates the relevant contents of genetic algorithm and its application in the optimal design of large-scale building structures and analyses and researches briefly several key factors when the genetic algorithm is applied to the optimal design of large-scale building structures, such as mathematical modelling, constraint condition treatment, generation of initial population and selection of control parameters of genetic algorithm. However, because the simple genetic algorithm is only good at global search, and the local search ability is not enough, it will take quite a long time to achieve the real optimal solution. For the shortcomings of simple genetic algorithm, an improved adaptive grey genetic algorithm is proposed in this paper. The example shows that the obtained adaptive genetic algorithm can improve the convergence and calculation speed when the genetic algorithms is applied to structural optimisation design.

Ultrasonic Computerized Tomography Imaging Method With Combinatorial Optimization Algorithm for Concrete Pile Foundation

Concrete pile foundations are the main load-carrying and aseismic structures for many large-scale building structures. Their structural quality will have a great impact on the safety of building structures. However, the imaging results still cannot easily meet practical demands in current ultrasonic Computerized Tomography (CT) imaging tests of concrete structures. In view of the current difficulties, a combinatorial optimization tomographic imaging method is proposed. First, a quadric broadening objective function with a clear physical meaning is established according to the characteristics of ultrasonic propagation in concrete. Then, a new CT imaging method of concrete pile foundation is formed by combining fast adaptive optimization search ability of Genetic Algorithm (GA) with the global search control ability of Simulated Annealing Algorithm (SAA). The numerical simulation experiments have shown that the usage of the correct priori information and the excellent characteristic of the Simulated Annealing Genetic Algorithm (SAGA) in searching for the global minimum value of the function have produced accurate and effective results with stable numerical values. Finally, the imaging method is verified by experiment, where results show that SAGA requires fewer iterations, has faster computation speed and gives more accurate imaging results compared with the single GA.

Decentralized control of tall buildings

The response of large-scale building structures can be actively reduced using an appropriate control algorithm and a number of actuators and sensors located within the building. This paper presents a decentralized control approach for controlling the response of tall buildings. The proposed method aims to divide the structural model into several substructures, each one performing on its own controller algorithm. This approach has already been used in controlling large-scale systems such as power transmission systems and space structures. An instantaneous optimal control scheme is used as the control algorithm with different control feedbacks such as velocity feedback alone and displacement and velocity feedback. The stability issue of this method is addressed. A numerical example is used to investigate the performance of the proposed method compared to the case with centralized control. Copyright © 2005 John Wiley & Sons, Ltd.