Zhaoshuo Jiang

A fully dynamic magneto-rheological fluid damper model

Control devices can be used to dissipate the energy of a civil structure subjected to dynamic loading, thus reducing structural damage and preventing failure. Semiactive control devices have received significant attention in recent years. The magneto-rheological (MR) fluid damper is a promising type of semiactive device for civil structures due to its mechanical simplicity, inherent stability, high dynamic range, large temperature operating range, robust performance, and low power requirements. The MR damper is intrinsically nonlinear and rate-dependent, both as a function of the displacement across the MR damper and the command current being supplied to the MR damper. As such, to develop control algorithms that take maximum advantage of the unique features of the MR damper, accurate models must be developed to describe its behavior for both displacement and current. In this paper, a new MR damper model that includes a model of the pulse-width modulated (PWM) power amplifier providing current to the damper, a proposed model of the time varying inductance of the large-scale 200 kN MR dampers coils and surrounding MR fluid—a dynamic behavior that is not typically modeled—and a hyperbolic tangent model of the controllable force behavior of the MR damper is presented. Validation experimental tests are conducted with two 200 kN large-scale MR dampers located at the Smart Structures Technology Laboratory (SSTL) at the University of Illinois at Urbana-Champaign and the Lehigh University Network for Earthquake Engineering Simulation (NEES) facility. Comparison with experimental test results for both prescribed motion and current and real-time hybrid simulation of semiactive control of the MR damper shows that the proposed MR damper model can accurately predict the fully dynamic behavior of the large-scale 200 kN MR damper. (Some figures may appear in colour only in the online journal)

Large-Scale Real-Time Hybrid Simulation for Evaluation of Advanced Damping System Performance

AbstractAs magnetorheological (MR) control devices increase in scale for use in real-world civil engineering applications, sophisticated modeling and control techniques may be needed to exploit their unique characteristics. Here, a control algorithm that utilizes overdriving and backdriving current control to increase the efficacy of the control device is experimentally verified and evaluated at large scale. Real-time hybrid simulation (RTHS) is conducted to perform the verification experiments using the nees@Lehigh facility. The physical substructure of the RTHS is a 10-m tall planar steel frame equipped with a large-scale MR damper. Through RTHS, the test configuration is used to represent two code-compliant structures, and is evaluated under seismic excitation. The results from numerical simulation and RTHS are compared to verify the RTHS methodology. The global responses of the full system are used to assess the performance of each control algorithm. In each case, the reduction in peak and root mean s...

A comparison of 200 kN magneto-rheological damper models for use in real-time hybrid simulation pretesting

Control devices can be used to dissipate the energy of a civil structure subjected to dynamic loading, such as earthquake, wave and wind excitation, thus reducing structural damage and preventing failure. The magneto-rheological (MR) fluid damper is a promising device for use in civil structures due to its mechanical simplicity, inherent stability, high dynamic range, large temperature operating range, robust performance, and low power requirements. The MR damper is intrinsically nonlinear and rate dependent. Thus a challenging aspect of applying this technology is the development of accurate models to describe the behavior of such dampers for control design and evaluation purposes. In particular, a new type of experimental testing called real-time hybrid simulation (RTHS) combines numerical simulation with laboratory testing of physical components. As with any laboratory testing, safety is of critical importance. For RTHS in particular the feedback and dynamic interaction of physical and numerical components can result in potentially unstable behavior. For safety purposes, it is desired to conduct pretest simulations where the physical specimen is replaced with an appropriate numerical model yet the numerical RTHS component is left unchanged. These pretest simulations require a MR damper model that can exhibit stability and convergence at larger fixed integration time steps, and provide computational efficiency, speed of calculation, and accuracy during pretest verification of the experimental setup. Several models for MR dampers have been proposed, including the hyperbolic tangent, Bouc?Wen, viscous plus Dahl and algebraic models. This paper examines the relative performance of four MR damper models of large-scale 200?kN MR dampers as needed for pretest simulations of RTHS. Experimental tests are conducted on two large-scale MR dampers located at two RTHS test facilities at the Smart Structures Technology Laboratory at the University of Illinois at Urbana Champaign and the Lehigh University Network for Earthquake Engineering Simulation facility. It is shown that each of the MR damper models examined has relative merits and the ultimate selection of the particular model is dependent on the specific RTHS being tested.

Real-time hybrid simulation of a complex bridge model with MR dampers using the convolution integral method

Magneto-rheological (MR) fluid dampers can be used to reduce the traffic induced vibration in highway bridges and protect critical structural components from fatigue. Experimental verification is needed to verify the applicability of the MR dampers for this purpose. Real-time hybrid simulation (RTHS), where the MR dampers are physically tested and dynamically linked to a numerical model of the highway bridge and truck traffic, provides an efficient and effective means to experimentally examine the efficacy of MR dampers for fatigue protection of highway bridges. In this paper a complex highway bridge model with 263 178 degrees-of-freedom under truck loading is tested using the proposed convolution integral (CI) method of RTHS for a semiactive structural control strategy employing two large-scale 200 kN MR dampers. The formation of RTHS using the CI method is first presented, followed by details of the various components in the RTHS and a description of the implementation of the CI method for this particular test. The experimental results confirm the practicability of the CI method for conducting RTHS of complex systems.

Implementation of a Probabilistic Structural Health Monitoring Method on a Highway Bridge

This paper describes the application of a probabilistic structural health monitoring (SHM) method to detect global damage in a highway bridge in Connecticut. The proposed method accounts for the variability associated with environmental and operational conditions. The bridge is a curved three-span steel dual-box girder bridge located in Hartford, Connecticut. The bridge, monitored since Fall 2001, experienced a period of settling in the Winter of 2002-2003. While this change was not associated with structural damage, it was observed in a permanent rotation of the bridge superstructure. Three damage measures are identified in this study: the value of fundamental natural frequency determined from peak picking of autospectral density functions of the bridge acceleration measurements; the magnitude of the peak acceleration measured during a truck crossing; the magnitude of the tilt measured at 10-minute intervals. These damage measures, including thermal effects, are shown to be random variables and associated P values are calculated to determine if the current probability distributions are the same as the distributions of the baseline bridge data from 2001. Historical data measured during the settling of the bridge is used to verify the performance of the bridge, and the field implementation of the proposed method is described.

Experimental Verification of an MR Damper Controlled Highway Bridge

There exists a current need in our nation to address the deteriorating integrity of our infrastructure. Highway bridges in particular are continuously approaching or exceeding their design life and are increasingly being classified as structurally deficient. The service life of highway bridges can be extended through the innovative application of structural control to reduce the peak stress in the critical elements of the bridge due to heavy truck traffic. A promising class of controllable hardware, the Magneto-Rheological (MR) damper, is proposed to reduce the dynamic response of bridges and extend the service life. The inherent stability, robust performance, and low power requirements of MR dampers make them an attractive type of controllable hardware for highway bridges. In this paper the large-scale real-time experimental verification of a typical highway bridge excited by a crossing truck and controlled with MR dampers using hybrid testing at the Lehigh University Network for Earthquake Engineering Simulation (NEES) facility is described. Preliminary simulation results indicate that peak and dynamic responses can be effectively reduced to increase the fatigue life of the structure. Initial experimental tests validate the simulations and indicate the potential of using MR dampers to reduce traffic induced vibration of bridge structures.

Energy-Efficient Heterogeneous Wireless Sensor Deployment with Multiple Objectives for Structural Health Monitoring

Heterogeneous wireless sensor networks (HWSNs) are widely adopted in structural health monitoring systems due to their potential for implementing sophisticated algorithms by integrating a diverse set of devices and improving a network’s sensing performance. However, deploying such a HWSN is still in a challenge due to the heterogeneous nature of the data and the energy constraints of the network. To respond to these challenges, an optimal deployment framework in terms of both modal information quality and energy consumption is proposed in this study. This framework generates a multi-objective function aimed at maximizing the quality of the modal information identified from heterogeneous data while minimizing the consumption of energy within the network at the same time. Particle swarm optimization algorithm is then implemented to seek solutions to the function effectively. After laying out the proposed sensor-optimization framework, a methodology is present to determine the clustering of the sensors to further conserve energy. Finally, a numerical verification is performed on a four-span pre-stressed reinforced concrete box-girder bridge. Results show that a set of strategically positioned heterogeneous sensors can maintain a balanced trade-off between the modal information accuracy and energy consumption. It is also observed that an appropriate cluster-tree network topology can further achieve energy saving in HWSNs.

Including Uncertainty in Modeling the Dynamic Response of a Large-Scale 200 kN Magneto-Rheological Damper

AbstractRealistic mathematical modeling is critical in engineering. Models help generalize experimental results, often suggest new experiments, and can replace costly physical testing. Most models, however, require validation of their parameters with experiment. For some models, parameters can be directly measured, but others must be inferred. In both cases parameters selection should reflect the inherent uncertainty in both measurement and modeling. This is particularly important for models used in control algorithms in which unexpected inputs may delay or prevent appropriate response. In this work, a method of characterizing uncertainty in model parameters is presented, the steps of the method are described in detail and illustrated using a case study application which models the force produced by a magneto-rheological (MR) damper. In this probabilistic approach, the model parameters are treated as random variables. The Metropolis-Hasting algorithm is used to generate sample parameter sets. These sets p...