Response of Lead Rubber Bearings in a Hybrid Isolation System During a Large Scale Shaking Experiment of an Isolated Building

AbstractResponse of Lead Rubber Bearings in a Hybrid Isolation System During a Large Scale Shaking Experiment of an Isolated BuildingByCamila Berton CoriaKeri L. Ryan, AdvisorSeismic isolation systems have been proven to provide superior performance and meet continued functionality performance objectives for many facilities around the world, and are thus being considered for the future generation of nuclear power plants in the United States. Experimental simulation of a hybrid lead-rubber isolation system for a 5-story steel moment frame was performed at Hyogo Earthquake Engineering Research Center (E-Defense) of the National Institute for Earth Science and Disaster Prevention in Japan. The isolation system was developed for the seismicity of a potential nuclear site in Central and Eastern United States (CEUS) site. The isolation system was tested to displacements representing beyond design basis ground motions at the CEUS site and design basis ground motions for a Western United States. Forces in the lead-rubber (LR) bearings were measured by an assembly of load cells. The design of the isolation system was constrained by the experimental setup. The light axial loads on the system necessitated the use of a hybrid system of elastomeric bearings and rolling bearings, known as cross linear (CL) bearings. The CL bearings provided support beneath some of the columns without contributing to the system base shear, so that the target displacement at the desired isolation period could be met. Additionally, the CL bearings provided substantial resistance against the tensile demands generated by overturning as a result of the light axial loads. The following behaviors, many of which have been observed before, were observed in the response of LR bearings during this test program: (1) pinching near the center of the measured bearing hysteresis loop, attributed to the small size of the lead plug; (2) loss of characteristic strength over the duration of an excitation, associated with heating of the lead plug; (3) no loss of shear resistance at large displacements due to the stabilizing influence of the CL bearings; and (4) transfer of axial forces from LR bearings to CL bearings at large displacements, referred to as the load transfer effect, causing the LR bearings to sustain tension that was not induced by overturning. The load transfer effect, occurs due to the rigidity of the frame system connecting the bearings, the discrepancy in stiffness between the CL and LR bearings in the vertical direction, and the effective decrease in stiffness of the LR bearings at large horizontal displacements.A numerical simulation model that represents current numerical approaches for design was developed for the isolation system and the structure. The lead-rubber bearings were modeled with a bilinear force-displacement relation with uncoupled behavior in the horizontal and vertical directions, referred as the uncoupled bearing model. Due to the amplitude dependence of the bearing response, the parameters of the uncoupled model were calibrated independently for each simulation to assess the experimental LR bearing response. Although the uncoupled bearing model could produce base shear and bearings displacements that closely matched the experimental response, the peak bearing responses (base shear and horizontal displacements) were not captured by the uncoupled bearing model. The revised bounding analysis methodology was investigated to determine if the peak bearings responses could be reliably bounded with this approach. The bounding analysis was not 100% reliable to bound the observed experimentally peak horizontal displacement and peak base shear of the LR bearings due to spectral variation of the excitations. However, the new bounding analysis procedure that considers the responses of both upper bound and lower bound to bound both peak displacements and peak forces, was found to be an improvement over current design practices. The uncoupled bearing model could not predict the load transfer effect that was observed during the experiment. Thus, a multi-spring LR bearing model with coupled behavior in the horizontal and vertical directions that could predict the load transfer effect was developed and validated. The numerically predicted horizontal responses obtained from the multi-spring bearing model and uncoupled bearing model were nearly identical.Significant portions of this dissertation were taken from a report (Ryan et al. 2013a) prepared for the sponsor one year following the test. The author of this dissertation worked collaboratively on that report with other authors. All data from the experiments is permanently archived and publicly accessible in the NEES Project Warehouse (Ryan et al. 2013b, 2013c, 2013d)

GSM based Communication-Sensor (CommSense) System

Using communication signals for radar applications has been a major area of research in radar engineering. In the recent years, due to the widely available wireless signals, a new area of research called commensal radars has emerged. Commensal radars use available wireless Radio Frequency (RF) signals to detect and track targets of interest. This is achieved by placing two antennas, one towards the transmitting base station and the other towards the surveillance area. The signal received by these two antennas are correlated to determine the location and velocity of the target. When a signal passes through a channel, it reflects off the obstacles within its path. These reflections usually degrade quality of the signal and cause interference to the telecommunication systems. To mitigate the effects of the channel on a signal these systems transmit a known bit sequence within each frame. Our goal, with this thesis, is to design and implement a working prototype of a novel architecture for the commensal radar system, which uses these known bit sequences to extract the channel information and determine events of interest. The major novelties of the system are as follows. Firstly, this system will be built upon existing communication systems using Software Defined Radio (SDR) technology. Secondly, this design eliminates the need for a reference antenna, which reduces the cost of the system and creates an opportunity to make the system portable. We name this system Communication-Sensing (CommSense). Since, our plan is to use Global System for Mobile Communication (GSM) as the parent system for the prototype development, we decide to update the name to GSM based Communication-Sensing (GSM-CommSense) system. This thesis begins with theoretical analysis of the feasibility of the GSM-CommSense system. First of all, we perform a link budget analysis to determine the power requirements for the system. Then we calculate the ambiguity function and Cram´er-Rao Lower Bound (CRLB) for a two-path received signal model. With encouraging theoretical results, we design a prototype of the system that can capture real GSM base station broadcast signals. After the design of the GSMCommSense system, we capture channel data from multiple locations with varying environmental conditions. The aim for this set of experiment is to be able to distinguish between different environmental conditions. Then, we performed statistical analysis on the data by means of Probability Density Function (PDF) fitting, a goodness-of-fit test called chi-square test and a clustering algorithm called Principal Components Analysis (PCA). We have presented the results from each analysis and discussed them in detail. Upon, receiving positive results in each step we have decided to move towards using learning algorithms to categorise the data captured by the system. We have compared two widely accepted supervised learning algorithms, called Support Vector Machines (SVM) and Multi-Layer Perceptron (MLP). The results showed that with the current hardware capabilities of the system and the amount of data available per GSM frame, the performance of SVM is better than MLP. Thus, we have used SVM to classify two events of detection and classification across a wall. We have presented our findings and discussed the results in detail. We conclude our current work and provide scope for future work in development and analysis of the GSM-CommSense system

Seismic Performance and Design of Bridge Foundations in Liquefiable Ground with a Frozen Crust

INE/AUTC 12.3

OBOE: Collaborative Filtering for AutoML Model Selection

Algorithm selection and hyperparameter tuning remain two of the most challenging tasks in machine learning. Automated machine learning (AutoML) seeks to automate these tasks to enable widespread use of machine learning by non-experts. This paper introduces OBOE, a collaborative filtering method for time-constrained model selection and hyperparameter tuning. OBOE forms a matrix of the cross-validated errors of a large number of supervised learning models (algorithms together with hyperparameters) on a large number of datasets, and fits a low rank model to learn the low-dimensional feature vectors for the models and datasets that best predict the cross-validated errors. To find promising models for a new dataset, OBOE runs a set of fast but informative algorithms on the new dataset and uses their cross-validated errors to infer the feature vector for the new dataset. OBOE can find good models under constraints on the number of models fit or the total time budget. To this end, this paper develops a new heuristic for active learning in time-constrained matrix completion based on optimal experiment design. Our experiments demonstrate that OBOE delivers state-of-the-art performance faster than competing approaches on a test bed of supervised learning problems. Moreover, the success of the bilinear model used by OBOE suggests that AutoML may be simpler than was previously understood

Building an Expert System for Evaluation of Commercial Cloud Services

Commercial Cloud services have been increasingly supplied to customers in industry. To facilitate customers' decision makings like cost-benefit analysis or Cloud provider selection, evaluation of those Cloud services are becoming more and more crucial. However, compared with evaluation of traditional computing systems, more challenges will inevitably appear when evaluating rapidly-changing and user-uncontrollable commercial Cloud services. This paper proposes an expert system for Cloud evaluation that addresses emerging evaluation challenges in the context of Cloud Computing. Based on the knowledge and data accumulated by exploring the existing evaluation work, this expert system has been conceptually validated to be able to give suggestions and guidelines for implementing new evaluation experiments. As such, users can conveniently obtain evaluation experiences by using this expert system, which is essentially able to make existing efforts in Cloud services evaluation reusable and sustainable.Comment: 8 page, Proceedings of the 2012 International Conference on Cloud and Service Computing (CSC 2012), pp. 168-175, Shanghai, China, November 22-24, 201