Torsion in base‐isolated structures with inelastic elastomeric isolation systems due to bidirectional lateral ground motion is studied. In a companion paper by the writers, torsional coupling in sliding base‐isolated structures was investigated. In this paper, which is the second part of the sequence, torsional coupling in elastomeric base‐isolated structures is investigated. Various multistoried structural systems with elastomeric isolation systems are investigated, with the objective of studying the influence of: (1) The flexibility of the superstructure; (2) the ratio of uncoupled torsional to lateral frequencies; (3) stiffness eccentricity in the superstructure; (4) eccentricity in the isolation system; (5) higher mode effects; and (6) number of bearings in the isolation system. Response to different ground motions is also studied. The results are used to explain: (1) The behavior of actual buildings; and (2) some inconsistencies in the conclusions of previous studies. It is shown that, although the total superstructure response is reduced significantly due to the effects of elastomeric base isolation, torsional amplification can be significant depending on the isolation and superstructure eccentricity and the lateral and torsional flexibility.
This study evaluates input error function observers for tracking of stiffness variation in real-time. The input error function is an Analytical Redundancy (AR)-based diagnosis method and necessitates a mathematical model of the system and system identification techniques. In practice, mathematical models used during numerical simulations differ from the actual status of the structure, and thus, accurate mathematical models are rarely available for reference. Noise is an unwanted signal in the input–output measurements but unavoidable in real-world applications (as in long span bridge trusses) and hard to imitate during numerical simulations. Simulation data from the truss system clearly indicates the effectiveness of the proposed structural damage detection method for estimating the severity of the damage. Optimization of the input error function can further automate the stiffness estimation in structural members and address critical aspects such as system uncertainties and the presence of noise in input–output measurements. Stiffness tracking in one of the planar truss members indicates the potential of optimization of the input error function for online structural health monitoring and implementing condition-based maintenance.
In this study, the real time strain response of the Multiwalled Carbon Nanotube (MWCNT) film to different kinds of tensile loading and response of the MWCNT film to temperature changes at macroscale is studied experimentally. The strain is applied to the MWCNT film by attaching it to a brass specimen using vacuum bonding, and subjecting it to tensile loading. Voltage output from MWCNT film is obtained using four-point probe in conjunction with a sensitive voltage measurement device. Experimental results demonstrate a linear relationship between change in voltage across the film and change in strain in the brass specimen when subjected to tensile load. The observed electromechanical characteristics also exhibit excellent reversibility evident from the way the voltage of the MWCNT film recovers to its unstressed state upon unloading. The MWCNT film exhibited a stable and linear response to changes in temperature with the resistance observed to be decreasing as temperature is increased. The study of MWCNT response to changes in temperature was done over a limited range. The experimental results presented in this paper demonstrate the effectiveness of MWCNT thin film in strain sensing as well as highlight the effect of temperature on it.
A negative stiffness device has been tested within a quarter-scale highway bridge model on the seismic shaking table at the University at Buffalo Network for Earthquake Engineering Simulation (NEES) site. Based on the experiments, numerical models have been developed, calibrated, and used to simulate the response of the bridge under a wide range of ground motions. In addition, performance indices have been developed to systematically and quantitatively evaluate the relative performance of different isolation system configurations that employ combinations of positive and negative stiffness as well as various levels of positive damping. Further, the influence of boundary conditions (rigid versus flexible bridge piers) on the effectiveness of employing negative stiffness devices has been evaluated. Finally, concepts for graphical interpretation of the performance indices are presented and used to demonstrate the degree to which employing negative stiffness may be beneficial in improving the seismic response of bridge structures.
The safety of deepwater risers is essential for sustainable operation of offshore platforms. The structural health monitoring (SHM) system for deepwater risers is important to detect damage and perform repairs before failure occurs. Two main sources of damage are fatigue and corrosion. Failure of the riser would not only be an economical and environmental disaster, but also have far reaching consequences affecting communities. Combining global and local monitoring can greatly increase the accuracy of damage detection and fatigue estimation. Local inspection using robotic Magnetic Flux leakage (MFL) sensors is efficient and provides high resolution estimate of wall thickness changes due to corrosion or damage, while proposed vibration-based system identification can estimate global damage locations and fatigue life. A new SHM system for deepwater risers was recently developed to monitor damage to the risers with both global and local monitoring methods proposed in this paper. The global monitoring is achieved by wavelet transform (WT) and second order blind identification (SOBI) method, from which, the likely location of fatigue damage is estimated. Once the location of the damage is identified by the proposed Wavelets/SOBI global identification method, local monitoring is performed using a robotic crawler with MFL sensors to further estimate the extent of the damage. Local monitoring with MFL sensors is verified by experimental results. Wavelets/SOBI global identification method is verified using Gulfstream test data. Possible applications for the proposed SHM systems are for deepwater risers and deepwater platforms. A robotic MFL crawler can be used for in-line inspection for various pipelines. The proposed damage detection method and fatigue estimation can be adapted to other offshore structures, both fixed and floating. The proposed global method can also be used to analyze Tensioned Leg Platforms (TLP). To demonstrate the applicability of the proposed Wavelets/SOBI method to risers and floating platforms, verification using Gulfstream riser field data and TLP model data is presented in the paper.
As the oil offloading operations of floating production storage and offloading (FPSO) units become more routine, the desire grows to increase the availability for offloading and thus decrease production downtime. Experience with these operations is the main tool available to increase the efficiency of this aspect of deepwater production. However, it is clear that a formal optimization approach can help to fine tune design parameters so that not only is availability increased but the significance of each design parameter can be better understood. The key issue is to define the environmental conditions under which the vessels involved in offloading are able to maintain position. By this, we reduce the notion of availability to a set of operating criteria, which can or cannot be met for a particular set of environmental conditions. The actual operating criteria such as relative vessel heading depend on selection of design parameters, such as the direction and magnitude of external force applied by thrusters or tugs. In the earliest offloading operations, engineering judgment was used to determine the feasibility of offloading at a particular time. For example, if wind and current were not expected to exceed a 1year return period, offloading may be considered safe. This approach can be both conservative and unconservative, depending on the nuances of the particular environmental conditions. This study will propose a formal approach to choosing the design parameters that optimize the availability of a FPSO for offloading. A simple analysis model will be employed so that optimization can be performed quickly using a robust second order method. The proposed analysis model will be compared to model test data to demonstrate its agreement with the more complex system.
Sparse system identification of nonlinear dynamic systems is still challenging, especially for stiff and high-order differential equations for noisy measurement data. The use of highly correlated functions makes distinguishing between true and false functions difficult, which limits the choice of functions. In this study, an equation discovery method has been proposed to tackle these problems. The key elements include a) use of B-splines for data fitting to get analytical derivatives superior to numerical derivatives, b) sequentially regularized derivatives for denoising (SRDD) algorithm, highly effective in removing noise from signal without system information loss, c) uncorrelated component analysis (UCA) algorithm that identifies and eliminates highly correlated functions while retaining the true functions, and d) physics-informed spline fitting (PISF) where the spline fitting is updated gradually while satisfying the governing equation with a dictionary of candidate functions to converge to the correct equation sequentially. The complete framework is built on a unified deep-learning architecture that eases the optimization process. The proposed method is demonstrated to discover various differential equations at various noise levels, including three-dimensional, fourth-order, and stiff equations. The parameter estimation converges accurately to the true values with a small coefficient of variation, suggesting robustness to the noise.
This paper deals with solution of nonlinear dynamic problems using Pseudo-force method. A solution algorithm involving Pseudo-force method is presented. The objective is to investigate the possibility of application of the method to highly nonlinear dynamic problems to which the method has not been applied to by previous investigators, such as problems with combined material and geometric nonlinearities, and problems with frictional nonlinearities. It is shown that Pseudo-force method is applicable in the above mentioned dynamic problems, by comparing the results with analytical and experimental results.
