Decentralized Networked Control of Building Structures

The article presents a new method for the design of decentralized networked switched controllers to mitigate the response of building structures under earthquakes. It consists of two phases. The first phase generates low‐order gain matrices based on the linear quadratic Gaussian (LQG) control design. It includes a substructural approach when the equations of motion of substructures are extracted from the equation of motion of the overall structures described by a finite element in‐plane (2‐D) model. Appropriate model reduction procedures, determination of damping as well as the selection of sensor and actuators locations and models are applied to each substructure. The sensors and actuators are implemented into the design model. Both resulting reduced‐order state space models of substructures are used for the proper LQG control design. The obtained local controllers are implemented into the overall structure to evaluate the performance of the closed‐loop system. Displacement, drift, acceleration, maximal actuator forces as well as dynamic responses on selected locations are checked. The computational originality is the method derived under the subsequent second phase, where the gain matrices computed in the first phase serve as a tool for the design of decentralized networked switched controller. The switching is realized periodically between two switched modes. Each mode corresponds with only one active local feedback loop for a certain period of time. The network parameter is the time interval of activity of each mode determined by a given protocol. Robustness of performance against packet dropouts and sensor faults is tested. A numerical example of the decentralized networked switched controller design applied on the 20‐story high‐fidelity building benchmark model is supplied. The simulation tests show the proposed method exhibits acceptable performance.     

A Modified Sliding Mode Fault Tolerant Control for Large‐Scale Civil Infrastructure

Adaptable active control strategies besides advance sensors and actuators technologies lead to higher performance of vibrational control in civil infrastructures under severe ground motions. These resilience control systems are robust against model uncertainties as well as being online recoverable from the malfunctioning of sensors and actuators. In this study, resilient control system based on sliding mode (SM) fault detection observer and SM fault tolerant control is improved for actuator fault in large‐scale systems. The SM fault detection observer is modified for eliminating the excessive chattering in estimating states and actuators’ fault, and the reconfigurable SM fault tolerant control is improved to minimizing input forces in control framework under seismic action. Design of observer and controller is performed using linear matrix inequalities. Numerical simulations on the cable‐stayed bridge benchmark demonstrate the effectiveness of the proposed fault‐tolerant system. Despite the high order of this large‐scale structure, the proposed fault detection and diagnosis method can effectively find the location and size of faults in actuators without performance degradation and computational costs. The fault‐tolerant controller maintains the performance of the structure at an acceptable level in the post‐fault case by redistribution of control signal to actuators.     

Optimal Mainline Variable Speed Limit Control to Improve Safety on Large‐Scale Freeway Segments

The primary objective of this study was to develop a procedure for determining the optimal variable speed limit (VSL) control strategy that aims at reducing both collision risks and injury severity on large‐scale freeway segments. The achieved reduction in collision risks and injury severity were evaluated using real‐time crash risk and severity prediction models. A modified cell transmission model (CTM) that took into consideration the capacity drop and the stop‐and‐go traffic was used to simulate the traffic operations with the VSL control. A computational procedure that incorporated the genetic algorithm and the CTM was proposed for the optimization of critical VSL control factors. Three scenarios with various placements of VSL signs on freeway mainlines were evaluated. The results showed that the optimal VSL control successfully decreased the collision risks by 22.62% and reduced the injury severity of crashes by 14.67%. We also evaluated how drivers’ compliance to speed limits affected the effectiveness of VSL control. The safety effects decreased as drivers’ compliance rate to the VSL control decreased. The finding suggests the use of speed enforcement techniques together with the VSL control to achieve the optimum control effects.     

Column Generation‐Based Approach for Solving Large‐Scale Ready Mixed Concrete Delivery Dispatching Problems

Ready mix concrete (RMC) dispatching forms a critical component of the construction supply chain. However, optimization approaches within the RMC dispatching continue to evolve due to the specific size, constraints, and objectives required of the application domain. In this article, we develop a column generation algorithm for vehicle routing problems (VRPs) with time window constraints as applied to RMC dispatching problems and examine the performance of the approach for this specific application domain. The objective of the problem is to find the minimum cost routes for a fleet of capacitated vehicles serving concrete to customers with known demand from depots within the allowable time window. The VRP is specified to cover the concrete delivery problem by adding additional constraints that reflect real situations. The introduced model is amenable to the Dantzig–Wolfe reformulation for solving pricing problems using a two‐staged methodology as proposed in this article. Further, under the mild assumption of homogeneity of the vehicles, the pricing sub‐problem can be viewed as a minimum‐cost multi‐commodity flow problem and solved in polynomial time using efficient network simplex method implementations. A large‐scale field collect data set is used for evaluating the model and the proposed solution method, with and without time window constraints. In addition, the method is compared with the exact solution found via enumeration. The results show that on average the proposed methodology attains near optimal solutions for many of the large sized models but is 10 times faster than branch‐and‐cut.     

A Two‐Dimension Dynamic Bayesian Network for Large‐Scale Degradation Modeling with an Application to a Bridges Network

Modeling the stochastic evolution of a large‐scale fleet or network generally proves to be challenging. This difficulty may be compounded through complex relationships between various assets in the network. Although a great number of probabilistic graph‐based models (e.g., Bayesian networks) have been developed recently to describe the behavior of single assets, one can find significantly fewer approaches addressing a fully integrated network. It is proposed an extension to the standard dynamic Bayesian network (DBN) by introducing an additional dimension for multiple elements. These elements are then linked through a set of covariates that translate the probabilistic dependencies. A Markov chain is utilized to model the elements and develop a distribution‐free mathematical framework to parameterize the transition probabilities without previous data. This is achieved by borrowing from Cooke's method for structured expert judgment and also applied to the quantification of the covariate relationships. Some metrics are also presented for evaluating the sensitivity of information inserted into the covariate DBN where the focus is given on two specific types of configurations. The model is applied to a real‐world example of steel bridge network in the Netherlands. Numerical examples highlight the inference mechanism and show the sensitivity of information inserted in various ways. It is shown that information is most valuable very early and decreases substantially over time. Resulting observations entail the reduction of inference combinations and by extension a computational gain to select the most sensitive pieces of information.     

A Time-Domain Algorithm for Active Control of Civil Structures

The objective of this study is to formulate and assess a simple time-domain control algorithm. The algorithm under consideration applies a control force to the structure at the current time step in order to cancel the portion of the system velocity that is induced by the response and the external load at the preceding time step. The effectiveness of the control algorithm is quantified using representative SDOF and MDOF test structures subjected to several earthquake time histories. The performance of the time-domain control algorithm is comparable with the performance of the classic linear quadratic regulator (LQR) formulation. Furthermore, the time-domain algorithm seems to be almost insensitive to uncertainties in the structural parameters and is able to accommodate practical limitations, such as maximum actuator capacity, without a drastic degradation in performance. Lastly, for MDOF structures, it is possible to develop and compare several control schemes depending on which velocities are selected to be independent of the response and loading at the previous time step.     

A Simple Active Control Algorithm for Earthquake Excited Structures

Abstract: A simple integral type quadratic functional is proposed as the performance index so that the optimal control policy is derived based on the minimization of the proposed performance index between the successive control instants by using the method of calculus of variations. The resulting optimal control law is applied to seismically excited linear buildings modeled as lumped mass shear frame structures. Active tendon actuators are considered as control devices. The performance of the proposed control (PC) is investigated when the example structure is subjected to three different seismic inputs and compared to the uncontrolled case and the classical linear optimal control (CLOC), which requires the solution of nonlinear matrix Riccati equation. It is shown by numerical simulation results that the PC is capable of suppressing the uncontrolled seismic vibrations of the linear structures and performs better than the CLOC.     

Active and Semi‐active Adaptive Control for Undamaged and Damaged Building Structures Under Seismic Load

Abstract: During the lifetime of a structural system, many severe events such as earthquakes and strong winds may impact the system and result in potential damage. To mitigate the structural vibration and damage during these extreme events, control devices such as active and semi‐active devices have received considerable attention because of their attractive characteristics. Active control devices are adaptable to any change and semi‐active devices have the capability of offering the reliability of passive devices and the versatility and adaptability of active devices. In this research, a direct‐adaptive‐control method is used to control the behavior of an undamaged and a damaged structure using semi‐active and active devices. In the adaptive control method, the controlled system is forced to behave like the model system which exhibits the desired behavior. The model of the adaptive control method is defined in a way to optimize the response of the controlled structure. The controller developed using this method can deal with changes that occur in the characteristics of the structure because it can modify its parameters during the control process. A magnetorheological (MR) damper is used as the semi‐active device in this study, whereas a hydraulic actuator is utilized as the active device to control the behavior of the structure. The performance of a three‐story building from the SAC project for the third generation of the control benchmark problem is studied by performing time–history analyses. The structure is subjected to different earthquakes and controlled by the direct adaptive control method. In the analysis of the structure, some stiffness reduction is assumed as a result of potential damage in the first story of the building. Also, the direct adaptive control strategy is used to optimize the response of the undamaged structure and to mitigate the damage impact on the performance of the controlled structure in the presence of noise for output measurements. The results of adaptive control method are compared with those of other control strategies. It is shown that the performance of the three‐story building is improved using the adaptive control method. By assessing the results of different control approaches, it is found that the adaptive control method works more effectively than other methods and semi‐active devices can provide reliable results.     

A Meta‐Heuristic Algorithm for Multi‐Objective Optimal Design of Hybrid Laminate Composite Structures

Abstract: In this article, we propose a meta‐heuristic algorithm for solving multi‐objective combinatorial optimization problems. The proposed multi‐objective combinatorial optimization algorithm is developed by combining the good features of popular guided local search algorithms like simulated annealing (SA) and tabu search (TS). It has been organized as a multiple start algorithm to maintain a good balance between intensification and diversification. The proposed meta‐heuristic algorithm is evaluated by solving the stacking sequence optimization of hybrid fiber‐reinforced composite plate, cylindrical shell, and pressure vessel problems. The standard performance metrics for evaluating multi‐objective optimization algorithms are used to demonstrate the effectiveness of the proposed algorithm over other popular evolutionary algorithms like Nondominated Sorting Genetic Algorithms (NSGA‐II), Pareto Archived Evolutionary Strategy (PAES), micro‐GA, and Multi‐Objective Particle Swarm Optimization (MOPSO).     

Evaluation of Information Applications of a Self‐Organizing Distributed Traffic Information System for a Large‐Scale Real‐World Traffic Network

Abstract: This article presents an evaluation of the system performance of a proposed self‐organizing, distributed traffic information system based on vehicle‐to‐vehicle information‐sharing architecture. Using microsimulation, several information applications derived from this system are analyzed relative to the effectiveness and efficiency of the system to estimate traffic conditions along each individual path in the network, to identify possible incidents in the traffic network, and to provide rerouting strategies for vehicles to escape congested spots in the network. A subset of vehicles in the traffic network is equipped with specific intervehicle communication devices capable of autonomous traffic surveillance, peer‐to‐peer information sharing, and self‐data processing. A self‐organizing traffic information overlay on the existing vehicular roadway network assists their independent evaluation of route information, detection of traffic incidents, and dynamic rerouting in the network based both on historical information stored in an in‐vehicle database and on real‐time information disseminated through intervehicle communications. A path‐based microsimulation model is developed for these information applications and the proposed distributed traffic information system is tested in a large‐scale real‐world network. Based on simulation study results, potential benefits both for travelers with such equipment as well as for the traffic system as a whole are demonstrated.     

A Two‐Step Model Updating Algorithm for Parameter Identification of Linear Elastic Damped Structures

A Frequency Response Functions (FRFs)‐based two‐step algorithm to identify stiffness, mass, and viscous damping matrices is developed in this work. The proposed technique uses the difference between the experimentally recorded FRF and their analytical counterparts by minimizing the resultant error function at selected frequency points. In the first step, only mass and stiffness matrices are updated while keeping the uncalibrated viscous damping matrix constant. In the second step, the damping matrix is updated via changes on the selected unknown modal damping ratios. By using a stacking procedure of the presented error function that combines multiple data sets, adverse effects of noise on the estimated modal damping ratios are decreased by averaging the FRF amplitudes at resonant peaks. The application of this methodology is presented utilizing experimentally obtained data. The presented algorithm can perform an accurate structural identification via model updating, with a viscous damping matrix that captures the variation of the modal damping ratios with natural frequencies as opposed to other conventional proportional damping matrix formulations.     

地震作用下结构振动瞬时最优控制的一种改进算法

模拟地震波输入结构的过程,在每一个时间步长建立控制目标函数,推导出了一种更为一般的瞬时最优控制算法,并用状态转移的数值方法加以实现.所获得的最优控制力表达式同时包含了当前时间步长初时刻结构响应和地震激励两部分的影响,从概念上改进了现有的瞬时最优控制算法;还导出了最优控制力系数表达式,用代数公式取代了传统的Riccati微分方程的求解,提高了计算效率.算例表明,该算法的控制效率优于现有的两种结构最优控制算法,具有更高的精度,且稳定性良好.     

Modal Response‐Based Visual System Identification and Model Updating Methods for Building Structures

This article proposes a new system identification (SI) method using the modal responses obtained from the dynamic responses of a structure for estimating modal parameters. Since the proposed SI method visually extracts the mode shape of a structure through the plotting of modal responses based on measured data points, the complex calculation process for the correlation and the decomposition for vibration measurements required in SI methods can be avoided. Also, without dependence on configurations of SI methods inducing variations of modal parameters, mode shapes and modal damping ratios can be stably extracted through direct implementation of modal response. To verify the feasibility of the proposed method, the modal parameters of a shear frame were extracted from modal displacement data obtained from a vibration test, and the results were compared with those obtained from the existing frequency domain SI method. The proposed method introduces the maximum modal response ratio of each mode computed by modal displacement data, and from this, the contribution of each mode and each measured location to the overall structural response is indirectly evaluated. Moreover, this article proposes a model updating method establishing the error functions based on the differences between the analytical model and measurement for the natural frequencies and the modal responses reflecting both mode shape and modal contribution. The validity of the proposed method is verified through the response prediction and modal contributions of the models obtained from model updating based on dynamic displacement from a shaking table test for a shear‐type test frame.     

Modal Identification for High‐Rise Building Structures Using Orthogonality of Filtered Response Vectors

The modal parameters of civil structures (natural frequency, mode shape, and mode damping ratio) are used for structural health monitoring (SHM), damage detection, and updating the finite element model. Long‐term measurement has been necessary to conduct operational modal analysis (OMA) under various loading conditions, requiring hundreds of thousands of discrete data points for estimating the modal parameters. This article proposes an efficient output‐only OMA technique in the form of filtered response vector (frv)‐based modal identification, which does not need complex signal processing and matrix operations such as singular value decomposition (SVD) and lower upper (LU) factorization, thus overcoming the main drawback of the existing OMA technique. The developed OMA technique also simplifies parameters such as window or averaging, which should be designed for signal processing by the OMA operator, under well‐separated frequencies and loading conditions excited by white noise. Using a simulation model and a 4‐story steel frame specimen, the accuracy and applicability were verified by comparing the dynamic properties obtained by the proposed technique and traditional frequency‐domain decomposition (FDD). In addition, the applicability and efficiency of the method were verified by applying the developed OMA to measured data, obtained through a field test on a 55‐story, 214‐m‐tall high‐rise building.     

建筑结构抗震鉴定刍议

几年来 ,对建筑结构的抗震鉴定有一些尝试 ,积累了较丰富的资料与经验。为了适应抗震鉴定规范的不断发展并推进建筑结构的抗震研究 ,通过几个实例说明抗震鉴定的目的、依据、内容等。同时还讨论了抗震鉴定工作中遇到的其他问题 ,以便更好地为工程建设及地震工程研究服务。     

大型商住楼的建筑消防设计实例

结合温州龙港商业中心工程实例,分别从总图、各个功能的防火分区、防烟分区、安全疏散、措施与构造等方面入手,介绍了大型商住楼建筑消防设计的思路和做法。     

Optimal Control of Adaptive/Smart Multistory Building Structures

This research advances creation of a new generation of adaptive/smart structures with self-modification capability by designing a predetermined number of members as actively controlled members. The computational model and high-performance parallel algorithms for optimal control of large structures recently developed by the authors are applied to multistory buildings. Four different schemes for placement of controllers are investigated. Three types of dynamic loadings are considered: earthquake ground motion, periodic impulsive horizontal wind loading on the exterior joints of the structure, and asymmetric periodic impulsive wind loading on the exterior of the structure modeling a twister. Results are presented for three multistory building structures with curved beams and setback representing both space moment-resisting and braced frames. It is demonstrated that through a proper selection of the weighting factor, the response of a multistory building structure can be reduced substantially to a fraction of the response of the uncontrolled structure at a practically feasible maximum required actuator force. Recommendations are made on the placement of the controllers for various types of structural configurations.     

Seismic Data‐Driven Identification of Linear Models for Building Structures Using Performance and Stabilizing Objectives

A two‐stage dual‐objective structural identification method is presented in this article. The complexity of the identification of story‐level physical models for large‐scale building structures is first addressed through a comparative study. A stiffness variation‐based stabilizing objective is proposed to be necessarily incorporated into iterative optimization with the classical performance objectives to improve the model feasibility, and an area‐type evaluation index is subsequently proposed for the stopping criteria. Accordingly, a two‐stage differential evolution‐based dual‐objective optimization framework is presented for the computation of Pareto fronts for nondominated candidate solutions. Then, the proposed method is investigated using two illustrative examples, including a nine‐story benchmark structure, and a real‐world seven‐story reinforced concrete structure. A series of condensed models are identified from the nondominated solutions on the Pareto front. The prediction performance of the single‐objective optimal model and the dual‐objective acceptable models is compared using the overall discrepancies of acceleration, interstory drift, and modal properties, within both estimation and validation cases. Incorporation of the noise effect into the method is finally studied and discussed.