Reconnaissance of Golcuk 1999 Earthquake Damage Using Satellite Images

This study utilizes remotely sensed pre- and post-disaster images in order to detect any change specifically associated with structural and major regional damage caused by natural disasters such as a strong earthquake. Currently, postdisaster reconnaissance is conducted using mostly ground-truth teams. Although by using this method high-resolution assessment can be provided, it is very time consuming, costly and sometimes not practical. This study investigates an unsupervised near near-time method of reconnaissance using a pair of coregistered remotely sensed images of the same scene acquired at different times as input. The output is an image (mostly binary) in which “changed” pixels are separated from “not-changed” ones. The approach is fully deterministic using principal component analysis, normalization and further setting a threshold to classify pixels. For verification, a set of multispectral images from Golcuk-Turkey 1999 earthquake was used. It is concluded the program generates very similar results as obtained by ground-truth teams.     

Damage Identification Using Electromagnetic Waves Based on Born Imaging Algorithm

Reconstructing damage geometry with computationally efficient and effective algorithms is of primary importance in establishing a robust structural health monitoring (SHM) system. In this paper, Born imaging algorithm is proposed for three-dimensional (3D) damage imaging of reinforced concrete structures using electromagnetic waves. This algorithm is derived in time domain for inhomogeneous isotropic and lossy structures. In order to reduce the computational cost of the algorithm, different imaging conditions are introduced. Numerical simulations in a 2D transverse magnetic case for a reinforced concrete slab with multiple damages are performed to test the effectiveness of the algorithm. In this simulated study, sensor data, incident field, and back-propagated field are computed via a finite difference time-domain method. It is concluded that the proposed imaging algorithm is capable of efficiently identifying the damages’ geometries and may be employed in a SHM system.     

Microwave Subsurface Imaging Technology for Damage Detection

This paper presents a technology for detecting invisible damage inside concrete, which is based on reconstruction of dielectric profile (image) of the concrete illuminated with microwaves sent from and received by antenna arrays controlled by specialized software. The imaging system developed in this study consists of an 8×8 transmitting and an 8×8 receiving arrays, an innovative numerical bifocusing operator for improving image resolution, and imaging software for reconstructing a two-dimensional image from the scattered field. The effectiveness of the developed technology in detecting steel and voids inside concrete has been demonstrated through numerical simulation and experiments.     

Object Recognition in Construction-Site Images Using 3D CAD-Based Filtering

Construction-site images that are now easily obtained from digital cameras have the potential to automatically provide the project status information. For example, once construction objects such as concrete columns are accurately identified and counted, the current level of project progress in the column installation activity can easily be measured. However, in order to identify and count the number of concrete columns installed at a particular point of time, a robust object recognition methodology is required. Without the successful recognition and extraction of the construction object of interest, it is almost impossible to understand the current level of project progress. This paper presents a robust image processing methodology to effectively extract the objects of interest from construction-site digital images. The proposed methodology makes use of advanced imaging algorithms and a three-dimensional computer aided design perspective view to increase the accuracy of the object recognition. Tests show that the methodology is promising and expected to provide a solid base for the successful, automatic acquisition of project information.     

Use of Microwaves for Damage Detection of Fiber Reinforced Polymer-Wrapped Concrete Structures

Jacketing technology using fiber reinforced polymer (FRP) composites is being applied for seismic retrofit and rehabilitation of reinforced concrete (RC) columns designed and constructed under older specifications. In this study, the authors develop an electromagnetic (EM) imaging technology for detecting such damage as voids and debonding between the jacket and the column, which may significantly weaken the structural performance of the column otherwise attainable by jacketing. This technology is based on the reflection analysis of a continuous EM wave sent toward and reflected from layered FRP–adhesive-concrete medium: Voids and debonding areas will generate air gaps which produce additional reflections of the EM wave. In this study, dielectric properties of various materials involved in the FRP-jacketed RC column were first measured using a plane-wave reflectometer. The measured properties were then used for a computer simulation of the proposed EM imaging technology. The simulation demonstrated the difficulty in detecting damage by using plane waves, as the reflection contribution from the voids and debonding is very small compared to that from the jacketed column. In order to alleviate this difficulty, dielectric lenses were designed and fabricated, focusing the EM wave on the bonding interface. Finally, three concrete columns were constructed and wrapped with glass–FRP jackets with various voids and debonding conditions artificially introduced in the bonding interface. Using the proposed EM imaging technology involving the especially designed and properly installed lenses, these voids and debonding areas were successfully detected. This technology can be used to assess the jacket bonding quality during the initial jacket installation stage and to detect debonding between the column and the jacket caused by earthquake and other destructive loads.     

Least-Squares Estimation with Unknown Excitations for Damage Identification of Structures

System identification and damage detection for structural health monitoring of civil infrastructures have received considerable attention recently. Time domain analysis methodologies based on measured vibration data, such as the least-squares estimation and the extended Kalman filter, have been studied and shown to be useful. The traditional least-squares estimation method requires that all the external excitation data (input data) be available, which may not be the case for many structures. In this paper, a recursive least-squares estimation with unknown inputs (RLSE-UI) approach is proposed to identify the structural parameters, such as the stiffness, damping, and other nonlinear parameters, as well as the unmeasured excitations. Analytical recursive solutions for the proposed RLSE-UI are derived and presented. This analytical recursive solution for RLSE-UI is not available in the previous literature. An adaptive tracking technique recently developed is also implemented in the proposed approach to track the variations of structural parameters due to damages. Simulation results demonstrate that the proposed approach is capable of identifying the structural parameters, their variations due to damages, and unknown excitations.     

Damage Detection in Composite Materials Using Identification Techniques

The present paper describes an approach for damage detection in composite structures that has its basis in methods of system identification. Response of a damaged structure differs from predictions obtained from a mathematical model of the original structure, where such a model is typically a finite‐element representation of the structure. In the present work dealing with composite materials, two distinct analytical models, one using two‐dimensional (2D) elements in conjunction with the classical lamination theory and another using three‐dimensional (3D) elements were considered. The output error approach of system identification was employed to determine changes in the analytical model necessary to minimize differences between the measured and predicted response. The proposed method is an extension of the stiffness‐reduction approach for damage detection to realistic structures. Numerical simulation of measurements of static deflections, strains, and vibration modes were used in the identification procedure. The methodology was implemented for representative composite structures. Principal shortcomings in the proposed approach and possible methods to circumvent these problems are discussed in the paper.     

On Parameter Estimation of Urban Storm-Water Runoff Model

An existing accumulation and wash-off model was applied and calibrated on a standard asphalt parking lot located in the northeastern United States. The field measured data consisted of rainfall, flow, and runoff samples taken from over 26 storm events monitored from 2004 to 2006. The contaminants under consideration include: total suspended solids, total petroleum hydrocarbons-diesel range hydrocarbons (TPH-D), dissolved inorganic nitrogen (DIN) (comprised of nitrate, nitrite, and ammonia), and zinc (Zn). The objective of the study was to provide probability distributions of model parameters for contaminants that have not been documented much (TPH-D, DIN, and Zn). The best fitting parameter values were found on a storm by storm basis. Subsequently, the range and variability of these parameters are provided for modeling purposes and other urban storm-water quality applications. A normal distribution was fitted to the optimized model parameter values to describe their distributions. A simulated annealing algorithm was used as the parameter optimization technique. Several examples are given to illustrate the methodology and the performance of the model. Finally, a Monte Carlo simulation was performed to assess the capability of the model to predict contaminant concentrations at the watershed’s outlet.     

Probabilistic Approach to Estimation of Urban Storm-Water Total Maximum Daily Loads: Unregulated Catchment

This work examines the basic processes and functions behind urban storm-water pollution delivery into surface waters and develops a set of tools that allow the estimation of pollutant load dynamics on receiving waters. In particular, the group of expressions developed in this paper allows the calculation of runoff parameters (volume, discharge rate and pollutant load) on an event average basis for an unregulated catchment. Using Monte Carlo simulation techniques, the runoff pollutant concentration probability distribution (as event averages) are obtained. Merging these runoff statistics with the stream parameters allows the receiving water pollutant concentration characteristics to be obtained as well as the probability of exceeding threshold pollutant concentrations in the mixing zone of a stream. The simulation can be performed with allowance for different levels of complexity with respect to catchment hydrologic representation and pollutant load functions. As a result, the magnitude of influence of urban runoff on a surface water body can be determined, pollutants of concern can be identified, and certain remedial measures recommended.     

Use of Supervisory Control and Data Acquisition for Damage Location of Water Delivery Systems

Urban water delivery systems can be damaged by earthquakes or severely cold weather. In either case, the damage cannot easily be detected and located, especially immediately after the event. In recent years, real-time damage estimation and diagnosis of buried pipelines attracted much attention of researchers focusing on establishing the relationship between damage ratio (breaks per unit length of pipe) and ground motion, taking the soil condition into consideration. Due to the uncertainty and complexity of the parameters that affect the pipe damage mechanism, it is not easy to estimate the degree of physical damage only with a few numbers of parameters. As an alternative, this paper develops a methodology to detect and locate the damage in a water delivery system by monitoring water pressure on-line at some selected positions in the water delivery systems. For the purpose of on-line monitoring, emerging supervisory control and data acquisition technology can be well used. A neural network-based inverse analysis method is constructed for detecting the extent and location of damage based on the variation of water pressure. The neural network is trained by using analytically simulated data from the water delivery system with one location of damage, and validated by using a set of data that have never been used in the training. It is found that the method provides a quick, effective, and practical way in which the damage sustained by a water delivery system can be detected and located.     

Statistical Damage Constitutive Model of Quasi-Brittle Materials

Recent studies have shown that statistical damage mechanics is one effective method to study the failure process of quasi-brittle materials. There are two key problems in setting up the statistical damage constitutive model of quasi-brittle materials, namely, determining the microunit strength and the parameters of statistical distribution that the microunit strength obeys. The four-parameter criterion is a failure criterion consisting of four unknown parameters. When the four parameters equal appropriate values, it may become the Drucker–Prager criterion (for rock), Mohr–Coulomb criterion (for rock), and Hsieh–Ting–Chen criterion (for concrete), so the four-parameter criterion may be used to simulate the elastoplastic behavior of rock and concrete quasi-brittle materials. In the paper, microunit strength is determined with the four-parameter criterion, thus the statistical damage constitutive model suits rock and concrete. The deficiencies of existing methods in determining the distribution parameters are investigated, and a new method for determining the distribution parameters is proposed. First, the theoretical relationships between the parameters and the strain and stress at the peak point of material failure curve are derived; second, the approximate relations between the strain and stress at the peak point of material failure curve and confining pressure are established through the curve fitting method; finally, the relations between the parameters and confining pressure are established. The proposed statistical damage softening constitutive model of quasi-brittle materials has universal meaning, the determination of distribution parameters has strict theoretical basis, and the distribution parameters can be conveniently obtained with general triaxial tests. Numerical examples are also presented to validate the model.     

Damage Localization and Finite-Element Model Updating Using Multiresponse NDT Data

New techniques for both finite-element model updating and damage localization are presented using multiresponse nondestructive test (NDT) data. A new protocol for combining multiple parameter estimation algorithms for model updating is presented along with an illustrative example. This approach allows for the simultaneous use of both static and modal NDT data to perform model updating at the element level. A new damage index based on multiresponse NDT data is presented for damage localization of structures. This index is based on static and modal strain energy changes in a structure as a result of damage. This method depicts changes in physical properties of each structural element compared to its initial state using NDT data. Deficient or potentially damaged structural elements are then selected as the unknown parameters to be updated by parameter estimation. Error function normalization, error function stacking, and multiresponse parameter estimation methods are proposed for using multiple data types for simultaneous stiffness and mass parameter estimation. Also, multiple sets of measurements with various sizes and missing data points can be utilized. This paper uses a laboratory grid model of a bridge deck built at the University of Cincinnati Infrastructure Institute and the corresponding NDT data for validation of the above damage localization and model updating methods. Multiresponse parameter estimation has been utilized to update the stiffness of bearing pads, and both the stiffness and mass of the connections, using static and dynamic NDT data. The static and modal responses of the updated grid model presented a closer match with the NDT data than the responses from the initial model.     

Structural Health Monitoring and Damage Assessment Using Frequency Response Correlation Criteria

Two frequency response correlation criteria, namely the global shape correlation (GSC) function and the global amplitude correlation (GAC) function, are established tools to quantify the correlation between predictions from a finite-element (FE) model and measured data for the purposes of FE model validation and updating. This paper extends the application of these two correlation criteria to structural health monitoring and damage detection. In addition, window-averaged versions of the GSC and GAC, namely WAIGSC and WAIGAC, are defined as effective damage indicators to quantify the change in structural response. An integrated method of structural health monitoring and damage assessment, based on the correlation functions and radial basis function neural networks, is proposed and the technique is applied to a bookshelf structure with 24 measured responses. The undamaged and damaged states, single and multiple damage locations, as well as damage levels, were successfully identified in all cases studied. The ability of the proposed method to cope with incomplete measurements is also discussed.     

Structural Damage Detection Using Empirical Mode Decomposition: Experimental Investigation

This paper presents an experimental investigation on the applicability of the empirical mode decomposition (EMD) for identifying structural damage caused by a sudden change of structural stiffness. A three-story shear building model was constructed and installed on a shaking table with two springs horizontally connected to the first floor of the building to provide additional structural stiffness. Structural damage was simulated by suddenly releasing two pretensioned springs either simultaneously or successively. Various damage severities were produced using springs of different stiffness. A series of free vibration, random vibration, and earthquake simulation tests were performed on the building with sudden stiffness changes. Dynamic responses including floor accelerations and displacements, column strains, and spring releasing time instants were measured. The EMD was then applied to measured time histories to identify damage time instant and damage location for various test cases. The comparison of identified results with measured ones showed that damage time instants could be accurately detected in terms of damage spikes extracted directly from the measurement data by EMD. The damage location could be determined by the spatial distribution of the spikes along the building. The influence of damage severity, sampling frequency, and measured quantities on the performance of EMD for damage detection was also discussed.     

Probabilistic Approach to Estimation of Urban Storm-Water TMDLs: Regulated Catchment

The present work is concerned with the development of a set of tools for the incorporation of various control measures—best management practices into an analytical probabilistic modeling approach for urban storm-water total maximum daily load (TMDL) estimation. Control measures are divided into two major groups—upstream and downstream, each requiring application of separate modeling principles elaborated in this paper. Applying Monte Carlo simulation to the developed set of expressions allows modeling the “end-of-pipe” parameters of urban storm-water discharges (runoff volume, discharge rate, and pollutant load) on an event average basis, as well as the stream parameters downstream of a storm-water discharge outlet. Model application is illustrated for a catchment regulated with an extended detention dry pond. Representative model results are presented, and a range of potential model applications is discussed. The capability to model the behavior of an urban storm-water system with the application of various control measures is the key precondition for the design of an optimal configuration of a water-protective strategy.     

Characterization of Damage in Triaxial Braided Composites under Tensile Loading

Carbon fiber composites that utilize flattened, large tow yarns in woven or braided forms are being used in many aerospace applications. The complex fiber architecture and large unit cell size in these materials present challenges for both understanding the deformation process and measuring reliable material properties. In this paper composites made using flattened 12k and 24k (referring to the number of fibers in the fiber tow) standard modulus carbon fiber yarns in a 0°/+60°/?60° triaxial braided architecture are examined. Standard straight-sided tensile coupons were tested with the 0° axial braid fibers either parallel to (axial tensile test) or perpendicular to (transverse tensile test) the applied tensile load. The nonuniform surface strain resulting from the triaxial braided architecture was examined using photogrammetry. Local regions of high strain concentration were examined to identify where failure initiates and to determine the local strain at the time of failure initiation. Splitting within fiber bundles was the first failure mode observed at low to intermediate strains. For axial tensile tests the splitting was primarily in the ±60° bias fibers, which were oriented 60° to the applied load. At higher strains in the axial tensile test, out-of-plane deformation associated with localized delamination between fiber bundles or damage within fiber bundles was observed. For transverse tensile tests, the splitting was primarily in the 0° axial fibers, which were oriented transverse to the applied load. The initiation and accumulation of local damage caused the global transverse stress-strain curves to become nonlinear and caused failure to occur at a reduced ultimate strain for both the axial and transverse tensile tests. Extensive delamination at the specimen edges was also observed. Modifications to the standard straight-sided coupon geometry are needed to minimize these edge effects when testing the large unit cell type of material examined in this work.     

Optimal Layout Design of a Satellite Module Using a Coevolutionary Method with Heuristic Rules

The layout design of a satellite module belongs to a three-dimensional (3D) packing problem with mutual-conflicting performance constraints. Taking the layout design of a simplified commercial communication satellite as a background, based on the cooperative coevolutionary framework, this paper presents a coevolutionary method with heuristic rules for the optimal layout design of a satellite module. First, a whole satellite module layout problem is decomposed into several sublayout problems according to the multisubphysical structure of a satellite module. Second, a relaxation model is adopted to distribute all objects among subspaces. Third, a coevolutionary genetic algorithm is adopted to solve the detailed layout design within the subspaces. Finally, a heuristic combination-rotation (CR) method is adopted to adjust the constraints to obtain the final whole layout scheme. Compared with the coevolutionary approach and the all-at-once optimization approaches, computational results show that the CR method can improve the computational accuracy of solutions and the proposed heuristic coevolutionary method can produces better solutions within short running times.     

Infiltration Capacity Assessment of Urban Pavements Using the LCS Permeameter and the CP Infiltrometer

This paper presents the Cantabrian portable infiltrometer (CP infiltrometer), a specially designed device based on rainfall simulation for the assessment of the infiltration capacity of all types of urban pavements. Several pervious and impervious surfaces were tested with the LCS permeameter, an existing infiltration test based on the use of a column of water, and the CP Infiltrometer, simulating rain intensities with return periods of 10, 50, and 500 years and 5?min duration. The discussion of the results indicates that the CP infiltrometer could be used successfully to identify different levels of infiltration capacity and to assess the correct performance of pervious surfaces on which design, construction, and maintenance decisions are based.     

Damage Evaluation with P-Wave Velocity Measurements during Uniaxial Compression Tests on Argillaceous Rocks

In the study of time dependent behavior of rock, the main difficulty is to predict delayed failure, which is of the utmost importance in assessing the safety of underground structures, such as deep underground facilities designed for high-level radioactive waste disposal. In this context, the viscoplastic behavior associated with the rock damage must be taken into account. As the longitudinal and transversal wave velocities are related to the physical and mechanical characteristics of materials, ultrasonic measurements can give valuable information about the development of damage. In this study, P-wave velocity measurements were used to monitor damage evolution during uniaxial strain in controlled compression tests and long-term creep tests. These measurements were performed using sensors in a piezoelectric copolymer of polyvinyl-difluoride, which were placed on both ends of cylindrical rock specimens. Throughout the experiments, the dilating behavior of an argillite could be correlated with a decrease of the P-wave velocity. Our results show that during a creep test, P-wave velocity measurements allow the three different phases of creep to be distinguished. During primary creep the P wave increases because of pore closure. The secondary creep phase, characterized by a constant strain rate, is identified by a linear decrease of the wave velocity; this trend accelerates during tertiary creep.     

Estimation of Crop Coefficients Using Satellite Remote Sensing

Crop coefficient (Kc) based estimation of crop evapotranspiration (ETc) is one of the most commonly used methods for irrigation water management. The standardized FAO56 Penman-Monteith approach for estimating ETc from reference evapotranspiration and tabulated generalized Kc values has been widely adopted worldwide to estimate ETc. In this study, we presented a modified approach toward estimating Kc values from remotely sensed data. The surface energy balance algorithm for land model was used for estimating the spatial distribution of ETc for major agronomic crops during the 2005 growing season in southcentral Nebraska. The alfalfa-based reference evapotranspiration (ETr) was calculated using data from multiple automatic weather stations with geostatistical analysis. The Kc values were estimated based on ETc and ETr (i.e., Kc = ETc/ETr). A land use map was used for sampling and profiling the Kc values from the satellite overpass for the major crops grown in southcentral Nebraska. Finally, a regression model was developed to establish the relationship between the normalized difference vegetation index (NDVI) and the ETr-based crop coefficients (Kcr) for corn, soybeans, sorghum, and alfalfa. We found that the coefficients of variation (CV) for NDVI, as well as for Kcr of crops were lower during the midseason as compared to the early and late growing seasons. High CV values during the early growing season can be attributed to differences in planting dates between the fields, whereas high CVs during the late season can be attributed to differences in maturity dates of the crops, variety, and management practices. There was a good relationship between Kcr and NDVI for all the crops except alfalfa. Validation of the developed model for irrigated corn showed very promising results. There was a good correlation between the NDVI-estimated Kcr and the Bowen ratio energy balance system based Kcr with a R2 of 0.74 and a low root mean square difference of 0.21. This approach can be a very useful tool for a large (watershed or regional) scale estimation of evapotranspiration using the crop coefficient and reference evapotranspiration approach.