Damage detection in civil structures using high-frequency seismograms

The dynamic properties of a structure are a function of its physical properties, and changes in the physical properties of the structure, including the introduction of structural damage, can cause changes in its dynamic behavior. Structural health monitoring (SHM) and damage detection methods provide a means to assess the structural integrity and safety of a civil structure using measurements of its dynamic properties. In particular, these techniques enable a quick damage assessment following a seismic event. In this thesis, the application of high-frequency seismograms to damage detection in civil structures is investigated.

Two novel methods for SHM are developed and validated using small-scale experimental testing, existing structures in situ, and numerical testing. The first method is developed for pre-Northridge steel-moment-resisting frame buildings that are susceptible to weld fracture at beam-column connections. The method is based on using the response of a structure to a nondestructive force (i.e., a hammer blow) to approximate the response of the structure to a damage event (i.e., weld fracture). The method is applied to a small-scale experimental frame, where the impulse response functions of the frame are generated during an impact hammer test. The method is also applied to a numerical model of a steel frame, in which weld fracture is modeled as the tensile opening of a Mode I crack. Impulse response functions are experimentally obtained for a steel moment-resisting frame building in situ. Results indicate that while acceleration and velocity records generated by a damage event are best approximated by the acceleration and velocity records generated by a colocated hammer blow, the method may not be robust to noise. The method seems to be better suited for damage localization, where information such as arrival times and peak accelerations can also provide indication of the damage location. This is of significance for sparsely-instrumented civil structures.

The second SHM method is designed to extract features from high-frequency acceleration records that may indicate the presence of damage. As short-duration high-frequency signals (i.e., pulses) can be indicative of damage, this method relies on the identification and classification of pulses in the acceleration records. It is recommended that, in practice, the method be combined with a vibration-based method that can be used to estimate the loss of stiffness. Briefly, pulses observed in the acceleration time series when the structure is known to be in an undamaged state are compared with pulses observed when the structure is in a potentially damaged state. By comparing the pulse signatures from these two situations, changes in the high-frequency dynamic behavior of the structure can be identified, and damage signals can be extracted and subjected to further analysis. The method is successfully applied to a small-scale experimental shear beam that is dynamically excited at its base using a shake table and damaged by loosening a screw to create a moving part. Although the damage is aperiodic and nonlinear in nature, the damage signals are accurately identified, and the location of damage is determined using the amplitudes and arrival times of the damage signal. The method is also successfully applied to detect the occurrence of damage in a test bed data set provided by the Los Alamos National Laboratory, in which nonlinear damage is introduced into a small-scale steel frame by installing a bumper mechanism that inhibits the amount of motion between two floors. The method is successfully applied and is robust despite a low sampling rate, though false negatives (undetected damage signals) begin to occur at high levels of damage when the frequency of damage events increases. The method is also applied to acceleration data recorded on a damaged cable-stayed bridge in China, provided by the Center of Structural Monitoring and Control at the Harbin Institute of Technology. Acceleration records recorded after the date of damage show a clear increase in high-frequency short-duration pulses compared to those previously recorded. One undamage pulse and two damage pulses are identified from the data. The occurrence of the detected damage pulses is consistent with a progression of damage and matches the known chronology of damage.

A bayesian probabilistic approach to structural health monitoring

A Bayesian probabilistic methodology for on-line structural health monitoring which addresses the issue of parameter uncertainty inherent in problem is presented. The method uses modal parameters for a limited number of modes identified from measurements taken at a restricted number of degrees of freedom of a structure as the measured structural data. The application presented uses a linear structural model whose stiffness matrix is parameterized to develop a class of possible models. Within the Bayesian framework, a joint probability density function (PDF) for the model stiffness parameters given the measured modal data is determined. Using this PDF, the marginal PDF of the stiffness parameter for each substructure given the data can be calculated.

Monitoring the health of a structure using these marginal PDFs involves two steps. First, the marginal PDF for each model parameter given modal data from the undamaged structure is found. The structure is then periodically monitored and updated marginal PDFs are determined. A measure of the difference between the calibrated and current marginal PDFs is used as a means to characterize the health of the structure. A procedure for interpreting the measure for use by an expert system in on-line monitoring is also introduced.

The probabilistic framework is developed in order to address the model parameter uncertainty issue inherent in the health monitoring problem. To illustrate this issue, consider a very simplified deterministic structural health monitoring method. In such an approach, the model parameters which minimize an error measure between the measured and model modal values would be used as the "best" model of the structure. Changes between the model parameters identified using modal data from the undamaged structure and subsequent modal data would be used to find the existence, location and degree of damage. Due to measurement noise, limited modal information, and model error, the "best" model parameters might vary from one modal dataset to the next without any damage present in the structure. Thus, difficulties would arise in separating normal variations in the identified model parameters based on limitations of the identification method and variations due to true change in the structure. The Bayesian framework described in this work provides a means to handle this parametric uncertainty.

The probabilistic health monitoring method is applied to simulated data and laboratory data. The results of these tests are presented.

DNA-mediated charge transport signaling within the cell

DNA possesses the curious ability to conduct charge longitudinally through the π-stacked base pairs that reside within the interior of the double helix. The rate of charge transport (CT) through DNA has a shallow distance dependence. DNA CT can occur over at least 34 nm, a very long molecular distance. Lastly, DNA CT is exquisitely sensitive to disruptions, such as DNA damage, that affect the dynamics of base-pair stacking. Many DNA repair and DNA-processing enzymes are being found to contain 4Fe-4S clusters. These co-factors have been found in glycosylases, helicases, helicase-nucleases, and even enzymes such as DNA polymerase, RNA polymerase, and primase across the phylogeny. The role of these clusters in these enzymes has remained elusive. Generally, iron-sulfur clusters serve redox roles in nature since, formally, the cluster can exist in multiple oxidation states that can be accessed within a biological context. Taken together, these facts were used as a foundation for the hypothesis that DNA-binding proteins with 4Fe-4S clusters utilize DNA-mediated CT as a means to signal one another to scan the genome as a first step in locating the subtle damage that occurs within a sea of undamaged bases within cells.

Herein we describe a role for 4Fe-4S clusters in DNA-mediated charge transport signaling among EndoIII, MutY, and DinG, which are from distinct repair pathways in E. coli. The DinG helicase is an ATP-dependent helicase that contains a 4Fe-4S cluster. To study the DNA-bound redox properties of DinG, DNA-modified electrochemistry was used to show that the 4Fe-4S cluster of DNA-bound DinG is redox-active at cellular potentials, and shares the 80 mV vs. NHE redox potential of EndoIII and MutY. ATP hydrolysis by DinG increases the DNA-mediated redox signal observed electrochemically, likely reflecting better coupling of the 4Fe-4S cluster to DNA while DinG unwinds DNA, which could have interesting biological implications. Atomic force microscopy experiments demonstrate that DinG and EndoIII cooperate at long range using DNA charge transport to redistribute to regions of DNA damage. Genetics experiments, moreover, reveal that this DNA-mediated signaling among proteins also occurs within the cell and, remarkably, is required for cellular viability under conditions of stress. Knocking out DinG in CC104 cells leads to a decrease in MutY activity that is rescued by EndoIII D138A, but not EndoIII Y82A. DinG, thus, appears to help MutY find its substrate using DNA-mediated CT, but do MutY or EndoIII aid DinG in a similar way? The InvA strain of bacteria was used to observe DinG activity, since DinG activity is required within InvA to maintain normal growth. Silencing the gene encoding EndoIII in InvA results in a significant growth defect that is rescued by the overexpression of RNAseH, a protein that dismantles the substrate of DinG, R-loops. This establishes signaling between DinG and EndoIII. Furthermore, rescue of this growth defect by the expression of EndoIII D138A, the catalytically inactive but CT-proficient mutant of EndoIII, is also observed, but expression of EndoIII Y82A, which is CT-deficient but enzymatically active, does not rescue growth. These results provide strong evidence that DinG and EndoIII utilize DNA-mediated signaling to process DNA damage. This work thus expands the scope of DNA-mediated signaling within the cell, as it indicates that DNA-mediated signaling facilitates the activities of DNA repair enzymes across the genome, even for proteins from distinct repair pathways.

In separate work presented here, it is shown that the UvrC protein from E. coli contains a hitherto undiscovered 4Fe-4S cluster. A broad shoulder at 410 nm, characteristic of 4Fe-4S clusters, is observed in the UV-visible absorbance spectrum of UvrC. Electron paramagnetic resonance spectroscopy of UvrC incubated with sodium dithionite, reveals a spectrum with the signature features of a reduced, [4Fe-4S]+1, cluster. DNA-modified electrodes were used to show that UvrC has the same DNA-bound redox potential, of ~80 mV vs. NHE, as EndoIII, DinG, and MutY. Again, this means that these proteins are capable of performing inter-protein electron transfer reactions. Does UvrC use DNA-mediated signaling to facilitate the repair of its substrates?

UvrC is part of the nucleotide excision repair (NER) pathway in E. coli and is the protein within the pathway that performs the chemistry required to repair bulky DNA lesions, such as cyclopyrimidine dimers, that form as a product of UV irradiation. We tested if UvrC utilizes DNA-mediated signaling to facilitate the efficient repair of UV-induced DNA damage products by helping UvrC locate DNA damage. The UV sensitivity of E. coli cells lacking DinG, a putative signaling partner of UvrC, was examined. Knocking out DinG in E. coli leads to a sensitivity of the cells to UV irradiation. A 5-10 fold reduction in the amount of cells that survive after irradiation with 90 J/m2 of UV light is observed. This is consistent with the hypothesis that UvrC and DinG are signaling partners, but is this signaling due to DNA-mediated CT? Complementing the knockout cells with EndoIII D138A, which can also serve as a DNA CT signaling partner, rescues cells lacking DinG from UV irradiation, while complementing the cells with EndoIII Y82A shows no rescue of viability. These results indicate that there is cross-talk between the NER pathway and DinG via DNA-mediated signaling. Perhaps more importantly, this work also establishes that DinG, EndoIII, MutY, and UvrC comprise a signaling network that seems to be unified by the ability of these proteins to perform long range DNA-mediated CT signaling via their 4Fe-4S clusters.