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.

New search for the Neutron Electric Dipole Moment using ultracold neutrons at the Spallation Neutron Source

This document introduces the planned new search for the neutron Electric Dipole Moment at the Spallation Neutron Source at the Oak Ridge National Laboratory. A spin precession measurement is to be carried out using Ultracold neutrons diluted in a superfluid Helium bath at T = 0.5 K, where spin polarized 3He atoms act as detector of the neutron spin polarization. This manuscript describes some of the key aspects of the planned experiment with the contributions from Caltech to the development of the project.

Techniques used in the design of magnet coils for Nuclear Magnetic Resonance were adapted to the geometry of the experiment. Described is an initial design approach using a pair of coils tuned to shield outer conductive elements from resistive heat loads, while inducing an oscillating field in the measurement volume. A small prototype was constructed to test the model of the field at room temperature.

A large scale test of the high voltage system was carried out in a collaborative effort at the Los Alamos National Laboratory. The application and amplification of high voltage to polished steel electrodes immersed in a superfluid Helium bath was studied, as well as the electrical breakdown properties of the electrodes at low temperatures. A suite of Monte Carlo simulation software tools to model the interaction of neutrons, 3He atoms, and their spins with the experimental magnetic and electric fields was developed and implemented to further the study of expected systematic effects of the measurement, with particular focus on the false Electric Dipole Moment induced by a Geometric Phase akin to Berry’s phase.

An analysis framework was developed and implemented using unbinned likelihood to fit the time modulated signal expected from the measurement data. A collaborative Monte Carlo data set was used to test the analysis methods.