A nonlinear data‐driven model for synthetic generation of annual streamflows

A hybrid model that blends two non‐linear data‐driven models, i.e. an artificial neural network (ANN) and a moving block bootstrap (MBB), is proposed for modelling annual streamflows of rivers that exhibit complex dependence. In the proposed model, the annual streamflows are modelled initially using a radial basis function ANN model. The residuals extracted from the neural network model are resampled using the non‐parametric resampling technique MBB to obtain innovations, which are then added back to the ANN‐modelled flows to generate synthetic replicates. The model has been applied to three annual streamflow records with variable record length, selected from different geographic regions, namely Africa, USA and former USSR. The performance of the proposed ANN‐based non‐linear hybrid model has been compared with that of the linear parametric hybrid model. The results from the case studies indicate that the proposed ANN‐based hybrid model (ANNHM) is able to reproduce the skewness present in the streamflows better compared to the linear parametric‐based hybrid model (LPHM), owing to the effective capturing of the non‐linearities. Moreover, the ANNHM, being a completely data‐driven model, reproduces the features of the marginal distribution more closely than the LPHM, but offers less smoothing and no extrapolation value. It is observed that even though the preservation of the linear dependence structure by the ANNHM is inferior to the LPHM, the effective blending of the two non‐linear models helps the ANNHM to predict the drought and the storage characteristics efficiently. Copyright © 2007 John Wiley & Sons, Ltd.     

Semi‐active fuzzy control for seismic response reduction using magnetorheological dampers

A semi‐active fuzzy control strategy for seismic response reduction using a magnetorheological (MR) damper is presented. When a control method based on fuzzy set theory for a structure with a MR damper is used for vibration reduction of a structure, it has an inherent robustness, and easiness to treat the uncertainties of input data from the ground motion and structural vibration sensors, and the ability to handle the non‐linear behavior of the structure because there is no longer the need for an exact mathematical model of the structure. For a clipped‐optimal control algorithm, the command voltage of a MR damper is set at either zero or the maximum level. However, a semi‐active fuzzy control system has benefit to produce the required voltage to be input to the damper so that a desirable damper force can be produced and thus decrease the control force to reduce the structural response. Moreover, the proposed control strategy is fail‐safe in that the bounded‐input, bounded‐output stability of the controlled structure is guaranteed. The results of the numerical simulations show that the proposed semi‐active control system consisting of a fuzzy controller and a MR damper can be beneficial in reducing seismic responses of structures. Copyright © 2004 John Wiley & Sons, Ltd.     

Characterization of fractured reservoirs using a consistent stiffness‐permeability model: focus on the effects of fracture aperture

In this paper we propose a method for the characterization of naturally fractured reservoirs by quantitative integration of seismic and production data. The method is based on a consistent theoretical frame work to model both effective hydraulic and elastic properties of fractured porous media and a (non‐linear) Bayesian method of inversion that provides information about uncertainties as well as mean (or maximum likelihood) values. We model a fractured reservoir as a porous medium containing a single set of vertical fractures characterized by an unknown fracture density, azimuthal orientation and aperture. We then look at the problem of fracture parameter estimation as a non‐linear inverse problem and try to estimate the unknown fracture parameters by joint inversion of seismic amplitude versus angle and azimuth data and dynamic production data. Once the fracture parameters have been estimated the corresponding effective stiffness and permeability tensors can be estimated using consistent models. A synthetic example is provided to clearly explain and test the workflow. It shows that seismic and production data complement each other, in the sense that the seismic data resolve a non‐uniqueness in the fracture orientation and the production data help to recover the true fracture aperture and permeability, because production data are more sensitive to the fracture aperture than the seismic data.     

Non‐iterative equivalent linearization of inelastic SDOF systems for earthquakes in Japan and California

The seismic performance of existing structures can be assessed based on nonlinear static procedures, such as the Capacity Spectrum Method. This method essentially approximates peak responses of an inelastic single‐degree‐of‐freedom (SDOF) system using peak responses of an equivalent linear SDOF model. In this study, the equivalent linear models of inelastic SDOF systems are developed based on the constant strength approach, which does not require iteration for assessing the seismic performance of existing structures. To investigate the effects of earthquake type and seismic region on the equivalent linear models, four ground‐motion data sets—Japanese crustal/interface/inslab records and California crustal records—are compiled and used for nonlinear dynamic analysis. The analysis results indicate that: (1) the optimal equivalent linear model parameters (i.e. equivalent vibration period ratio and damping ratio) decrease with the natural vibration period, whereas they increase with the strength reduction factor; (2) the impacts of earthquake type and seismic region on the equivalent linear model parameters are not significant except for short vibration periods; and (3) the degradation and pinching effects affect the equivalent linear model parameters. We develop prediction equations for the optimal equivalent linear model parameters based on nonlinear least‐squares fitting, which improve and extend the current nonlinear static procedure for existing structures with degradation and pinching behavior. Copyright © 2010 John Wiley & Sons, Ltd.     

Application of non‐linear multiple tuned mass dampers to suppress man‐induced vibrations of a pedestrian bridge

This paper presents an application of multiple tuned mass dampers (MTMDs) with non‐linear damping devices to suppress man‐induced vibrations of a 34m long pedestrian bridge. The damping force generated by each of these damping devices is simply a drag force from liquid acting on an immersed section. The quadratic non‐linear property of these devices was directly determined from free vibration tests of a simple laboratory set‐up. Dynamic models of the bridge and pedestrian loads were constructed for numerical investigation based on field measurement data. The control effectiveness of non‐linear MTMDs was examined along with its sensitivity against estimation errors in the bridge's natural frequency and magnitude of pedestrian load. The numerical results indicated that the optimum non‐linear MTMD system was as effective and robust as its linear counterpart. Then, a six‐unit non‐linear MTMD system was designed, constructed, and installed on the bridge. Field measurements after the installation confirmed the effectiveness of non‐linear MTMDs, and the measurement results were in good agreement with numerical predictions. After the installation, the average damping ratio of the bridge was raised from 0.005 to 0.036 and the maximum bridge accelerations measured during walking tests were reduced from about 0.80–1.30 ms^?2 to 0.27–0.40 ms^?2, which were within an acceptable range. Copyright © 2003 John Wiley & Sons, Ltd.     

Parameter identification of framed structures using an improved finite element model‐updating method—Part II: application to experimental data

In this study, we determine an updated finite element model of a reinforced concrete building—which was damaged from shaking during 1994 Northridge earthquake—using forced‐vibration test data and a novel model‐updating technique. Developed and verified in the companion paper (viz. BVLSrc, Earthquake Eng. Struct. Dyn. 2006; this issue), this iterative technique incorporates novel sensitivity‐based relative constraints to avoid ill conditioning that results from spatial incompleteness of measured data. We used frequency response functions and natural frequencies as input for the model‐updating problem. These data were extracted from measurements obtained during a white‐noise excitation applied at the roof of the building using a linear inertial shaker. Flexural stiffness values of properly grouped structural members, modal damping ratios, and translational and rotational mass values were chosen as the updating parameters, so that the converged results had direct physical interpretations, and thus, comparisons with common parameters used in seismic design and evaluation of buildings could be made. We investigated the veracity of the updated finite element model by comparing the predicted and measured dynamic responses under a second, and different type of forced (sine‐sweep) vibration, test. These results indicate that the updated model replicates the dynamic behaviour of the building reasonably well. Furthermore, the updated stiffness factors appear to be well correlated with the observed building damage patterns (i.e. their location and severity). Copyright © 2006 John Wiley & Sons, Ltd.     

Predicting catchment flow in a semi‐arid region via an artificial neural network technique

A model of rainfall–runoff relationships is an essential tool in the process of evaluation of water resources projects. In this paper, we applied an artificial neural network (ANN) based model for flow prediction using the data for a catchment in a semi‐arid region in Morocco. Use of this method for non‐linear modelling has been demonstrated in several scientific fields such as biology, geology, chemistry and physics. The performance of the developed neural network‐based model was compared against multiple linear regression‐based model using the same observed data. It was found that the neural network model consistently gives superior predictions. Based on the results of this study, artificial neural network modelling appears to be a promising technique for the prediction of flow for catchments in semi‐arid regions. Accordingly, the neural network method can be applied to various hydrological systems where other models may be inappropriate. Copyright © 2004 John Wiley & Sons, Ltd.     

System identification of the Vincent Thomas suspension bridge using earthquake records

The Vincent Thomas Bridge in the Los Angeles metropolitan area, is a critical artery for commercial traffic flow in and out of the Los Angeles Harbor, and is at risk in the seismically active Southern California region, particularly because it straddles the Palos Verdes fault zone. A combination of linear and non‐linear system identification techniques is employed to obtain a complete reduced‐order, multi‐input–multi‐output (MIMO) dynamic model of the Vincent Thomas Bridge based on the dynamic response of the structure to the 1987 Whittier and 1994 Northridge earthquakes. Starting with the available acceleration measurements (which consists of 15 accelerometers on the bridge structure and 10 accelerometers at various locations on its base), an efficient least‐squares‐based time‐domain identification procedure is applied to the data set to develop a reduced‐order, equivalent linear, multi‐degree‐of‐freedom model. Although not the main focus of this study, the linear system identification method is also combined with a non‐parametric identification technique, to generate a reduced‐order non‐linear mathematical model suitable for use in subsequent studies to predict, with good fidelity, the total response of the bridge under arbitrary dynamic environments. Results of this study yield measurements of the equivalent linear modal properties (frequencies, mode shapes and non‐proportional damping) as well as quantitative measures of the extent and nature of non‐linear interaction forces arising from strong ground shaking. It is shown that, for the particular subset of observations used in the identification procedure, the apparent non‐linearities in the system restoring forces are quite significant, and they contribute substantially to the improved fidelity of the model. Also shown is the potential of the identification technique under discussion to detect slight changes in the structure's influence coefficients, which may be indicators of damage and degradation in the structure being monitored. Difficulties associated with accurately estimating damping for lightly damped long‐span structures from their earthquake response are discussed. The technical issues raised in this paper indicate the need for added spatial resolution in sensor instrumentation to obtain identified mathematical models of structural systems with the broadest range of validity. Copyright © 2003 John Wiley & Sons, Ltd.     

Structural impedance based damage diagnosis by piezo‐transducers

Although structural mechanical impedance is a direct representation of the structural parameters, its measurement is difficult at high frequencies owing to practical considerations. This paper presents a new method of damage diagnosis by means of changes in the structural mechanical impedance at high frequencies. The mechanical impedance is extracted from the electro‐mechanical admittance signatures of piezoelectric‐ceramic (PZT) patches surface bonded to the structure using the electro‐mechanical impedance (EMI) technique. The main feature of the newly developed approach is that both the real as well as the imaginary component of the admittance signature is used in damage quantification. A complex damage metric is proposed to quantify damage parametrically based on the extracted structural parameters, i.e. the equivalent single degree of freedom (SDOF) stiffness, the mass, and the damping associated with the drive point of the PZT patch. The proposed scheme eliminates the need for any a priori information about the phenomenological nature of the structure or any ‘model’ of the structural system. As proof of concept, the paper reports a damage diagnosis study conducted on a model reinforced concrete (RC) frame subjected to base vibrations on a shaking table. The proposed methodology was found to perform better than the existing damage quantification approaches, i.e. the low‐frequency vibration methods as well as the traditional raw‐signature based damage quantification in the EMI technique. Copyright © 2003 John Wiley & Sons, Ltd.     

Evaluation of predictors of non‐linear seismic demands using ‘fishbone’ models of SMRF buildings

Predictors (or estimates) of seismic structural demands that are less computationally time‐consuming than non‐linear dynamic analysis can be useful for structural performance assessment and for design. In this paper, we evaluate the bias and precision of predictors that make use of, at most, (i) elastic modal vibration properties of the given structure, (ii) the results of a non‐linear static pushover analysis of the structure, and (iii) elastic and inelastic single‐degree‐of‐freedom time‐history analyses for the specified ground motion record. The main predictor of interest is an extension of first‐mode elastic spectral acceleration that additionally takes into account both the second‐mode contribution to (elastic) structural response and the effects of inelasticity. This predictor is evaluated with respect to non‐linear dynamic analysis results for ‘fishbone’ models of steel moment‐resisting frame (SMRF) buildings. The relatively small number of degrees of freedom for each fishbone model allows us to consider several short‐to‐long period buildings and numerous near‐ and far‐field earthquake ground motions of interest in both Japan and the U.S. Before doing so, though, we verify that estimates of the bias and precision of the predictor obtained using fishbone models are effectively equivalent to those based on typical ‘full‐frame’ models of the same buildings. Copyright © 2003 John Wiley & Sons, Ltd.     

A new modelling strategy for the behaviour of shear walls under dynamic loading

A new simplified modelling strategy to simulate the non‐linear behaviour of reinforced concrete shear walls under dynamic loading is presented. The equivalent reinforced concrete (ERC) model is derived from the framework method and uses lattice meshes for concrete and reinforcement bars and uniaxial constitutive laws based on continuum damage mechanics and plasticity. Results show the capacity of the model to analyse structures having different slenderness and boundary conditions. For low reinforcement ratios however, results are sensitive to the angle formed by the diagonals of the concrete lattice and the horizontal bars. The method is compared with the shear multi‐layered beam model that uses Timoshenko multi‐layered 2D beam elements and biaxial constitutive laws. Comparisons for both models with experimental results of two research programs (one organized by NUPEC and the other by COGEMA and EDF) are provided. ERC is a simplified method that intends to save computer time and allows parametrical studies. Copyright © 2002 John Wiley & Sons, Ltd.     

Damage identification of a 3D full scale steel–concrete composite structure with partial‐strength joints at different pseudo‐dynamic load levels

Partial‐strength composite steel–concrete moment‐resisting (MR) frame structures represent an open research field in seismic design from both a theoretical and an experimental standpoint. Among experimental techniques, vibration testing is a well‐known and powerful technique for damage detection, localization and quantification, where actual modal parameters of a structure at different states can be determined from test data by using system identification methods. However, the identification of semi‐rigid connections in framed structures is limited, and hence this paper focuses on a series of vibration experiments that were carried out on a realistic MR frame structure, following the application of pseudo‐dynamic and quasi‐static cyclic loadings at the European laboratory for structural assessment of the Joint Research Centre at Ispra, Italy, with the scope of understanding the structural behaviour and identifying changes in the dynamic response. From the forced vibration response, natural frequencies, damping ratios, modal displacements and rotations were extracted using the circle fitting technique. These modal parameters were used for local and global damage identification by updating a 3D finite element model of the intact structure. The identified results were then correlated with observations performed on the structure to understand further the underlying damage mechanisms. Finally, the latin hypercube sampling technique, a variant of the Monte Carlo method, was employed in order to study the sensitivity of the updated parameters of the 3D model to noise on the modal inputs. Copyright © 2009 John Wiley & Sons, Ltd.     

Evaluation of site‐dependent constant‐damage design spectra for reinforced concrete structures

An investigation on the validity of the conventional design approach known as constant displacement ductility is carried out. The hysteretic behaviour described by the Modified Takeda model is taken to represent the characteristics of reinforced concrete structural systems. The results presented in the form of seismic damage spectra indicate that the conventional design approach may not be valid because cumulative damage is excessively high. The inelastic design spectra based on the constant‐damage concept are proposed in terms of simplified expressions. The expressions are derived from constant‐damage design spectra computed by non‐linear response analysis for SDOF systems subjected to ground motions recorded on rock sites, alluvium deposits, and soft‐soil sites. The proposed expressions, which are dependent on the local soil conditions, are functions of target seismic damage, displacement ductility ratio and period of vibration. The seismic damage of structures that have been designed based on this new design approach is also checked by a design‐and‐evaluation approach. The results are found to be satisfactory. Copyright © 2004 John Wiley & Sons, Ltd.     

System identification and damage evaluation of degrading hysteresis of reinforced concrete frames

In this study, signal processing approaches and nonlinear identification are used to measure seismic responses of reinforced concrete (RC) structures using the shaking table test. To analyze structural nonlinearity, an equivalent linear system with time‐varying model parameters, singular spectrum analysis to elucidate residual deformation, and wavelet packet transformation analysis to yield the energy distribution among components are adopted to detect the nonlinearity. Then, damage feature extraction is conducted using both the Holder exponent and the Level‐1 detail of the discrete wavelet component. Finally, the modified Bouc‐Wen hysteretic model and the system identification process are employed to the shaking table test data to evaluate the physical parameters, including the stiffness degradation, the strength deterioration and the pinching hysteresis. Finally, the identified stiffness and strength degradation functions from the test data of RC frames in relation to the degree of ground shaking, damage index and the identified nonlinear features are discussed. Based on the proposed method, both signal‐based and model‐based identifications, the relationship between the damage occurrence and severity of structural damage can be identified. Copyright © 2010 John Wiley & Sons, Ltd.     

Earthquake response analysis of the Hualien soil–structure interaction system based on updated soil properties using forced vibration test data

This paper presents results of the earthquake response analysis on a large‐scale seismic test (LSST) structure which was built at Hualien in Taiwan for an international cooperative research project. The analysis is carried out using a computer program which has been developed based on axisymmetric finite element method incorporating dynamic infinite elements for far‐field soil region and a substructured wave input technique. The non‐linear behaviour of the soil medium is taken into account using an iterative equivalent linearization procedure. Two sets of the soil and structural properties, namely the unified and the FVT‐correlated models, are utilized as the initial linear values. The unified model was provided by a group of experts in charge of the geotechnical experiments, and the correlated model was obtained through a system identification procedure using the forced vibration test (FVT) results by the present authors. Three components of ground accelerations are artificially generated through an averaging process of the Fourier amplitude spectra of the ground accelerations measured near the test structure, and they are used as the control input motions for the earthquake analysis. It has been found that the earthquake responses predicted using the generated control motions and with the FVT‐correlated model as the initial linear properties in the equivalent linearization procedure compare very well with the observed responses. Copyright © 2001 John Wiley & Sons, Ltd.     

Efficient seismic response data storage and transmission using ARX model‐based sensor data compression algorithm

This paper presents a linear predictor (LP)‐based lossless sensor data compression algorithm for efficient transmission, storage and retrieval of seismic data. Auto‐Regressive with eXogenous input (ARX) model is selected as the model structure of LP. Since earthquake ground motion is typically measured at the base of monitored structures, the ARX model parameters are calculated in a system identification framework using sensor network data and measured input signals. In this way, sensor data compression takes advantage of structural system information to maximize the sensor data compression performance. Numerical simulation results show that several factors including LP order, measurement noise, input and limited sensor number affect the performance of the proposed lossless sensor data compression algorithm concerned. Generally, the lossless data compression algorithm is capable of reducing the size of raw sensor data while causing no information loss in the sensor data. Copyright © 2005 John Wiley & Sons, Ltd.     

A macro‐element model for non‐linear soil–shallow foundation–structure interaction under seismic loads: theoretical development and experimental validation on large scale tests

In this paper, different formulations of a macro‐element model for non‐linear dynamic soil‐structure interaction analyses of structures lying on shallow foundations are first reviewed, and secondly, a novel formulation is introduced, which combines some of the characteristics of previous approaches with several additional features. This macro‐element allows one to model soil‐footing geometric (uplift) and material (soil plasticity) non‐linearities that are coupled through a stiffness degradation model. Footing uplift is introduced by a simple non‐linear elastic model based on the concept of effective foundation width, whereas soil plasticity is treated by means of a bounding surface approach in which a vertical load mapping rule is implemented. This mapping is particularly suited for the seismic loading case for which the proposed model has been conceived. The new macro‐element is subsequently validated using cyclic and dynamic large‐scale laboratory tests of shallow foundations on dense sand, namely: the TRISEE cyclic tests, the Public Works Research Institute and CAMUS IV shaking table tests. Based on this comprehensive validation process against a set of independent experimental results, a unique set of macro‐element parameters for shallow foundations on dense sand is proposed, which can be used to perform predictive analyses by means of the present model. Copyright © 2011 John Wiley & Sons, Ltd.     

System identification on the seismic behavior of an isolated bridge

Seismic isolation devices and technology have been developed in the last two decades and the first seismic‐isolated bridge, Bai‐Ho Bridge, in Taiwan was completed in 1999. This bridge was equipped with a seismic monitoring system under the Taiwan Strong Motion Instrumentation Program (TSMIP). On 22 October 1999, a moderate earthquake took place and struck the bridge. The seismic monitoring sensors were normally triggered and produced an intact time history for the health monitoring of the bridge system. The data set provided valuable records about the seismic response of the isolation bridge structure. This paper uses this data to explore the vibration mechanism of Bai‐Ho Bridge. The analysis includes (1) the global dynamic behavior identification and (2) the local component mechanism of the bridge such as the LRB and boundary condition between the deck and the abutments. Both the EMD+HHT method and the non‐linear parametric model were used to identify the model of the bridge structure. Copyright © 2003 John Wiley & Sons, Ltd.     

Semi‐explicit rate‐dependent modeling of damage‐avoidance steel connections using HF2V damping devices

A rate‐dependent modeling technique is developed for moment resisting steel connections that utilize non‐linear viscous dampers. First, a model of the Maxwell‐type is developed that considers the non‐linear viscous damper and connection flexibility for translational motion. This model is compared with experimental results at several input motion frequencies to validate the results. The model is then extended to represent an exterior steel beam‐to‐column connection using damage‐avoidance design and non‐linear viscous dampers. By including terms to represent structural member and connection flexibility, using appropriate geometric transformations the model can be formulated to give the overall lateral load‐drift structural performance. Validation analysis shows good agreement between experimental observations and the model predictions. Copyright © 2010 John Wiley & Sons, Ltd.     

Parameter identification of framed structures using an improved finite element model‐updating method—Part I: formulation and verification

In this study, we formulate an improved finite element model‐updating method to address the numerical difficulties associated with ill conditioning and rank deficiency. These complications are frequently encountered model‐updating problems, and occur when the identification of a larger number of physical parameters is attempted than that warranted by the information content of the experimental data. Based on the standard bounded variables least‐squares (BVLS) method, which incorporates the usual upper/lower‐bound constraints, the proposed method (henceforth referred to as BVLSrc) is equipped with novel sensitivity‐based relative constraints. The relative constraints are automatically constructed using the correlation coefficients between the sensitivity vectors of updating parameters. The veracity and effectiveness of BVLSrc is investigated through the simulated, yet realistic, forced‐vibration testing of a simple framed structure using its frequency response function as input data. By comparing the results of BVLSrc with those obtained via (the competing) pure BVLS and regularization methods, we show that BVLSrc and regularization methods yield approximate solutions with similar and sufficiently high accuracy, while pure BVLS method yields physically inadmissible solutions. We further demonstrate that BVLSrc is computationally more efficient, because, unlike regularization methods, it does not require the laborious a priori calculations to determine an optimal penalty parameter, and its results are far less sensitive to the initial estimates of the updating parameters. Copyright © 2006 John Wiley & Sons, Ltd.