153 publications from this institution
A field investigation was conducted near the town of Bala after two strong earthquakes struck the region on December 20 and 27, 2007. The main objectives of this study are to present the results of the field investigation and examine the characteristics of the recorded ground motions and the corresponding response spectra. The focus of the research was on the causes of damage and failures commonly observed in masonry structures. This study classifies single family masonry dwellings in rural areas and investigates the seismic damage in unreinforced masonry structures. Turkish Earthquake Code requirements for masonry buildings are summarized and compared with the field observations. Our field investigation showed that there has been lack of quality control and regulation for the masonry construction. Diagonal shear cracking and out-of-plane failure were the two major factors that contributed to widespread damage in masonry structures.
Predicting the shear strength of structural elements subjected to gravity loads and ground motions is an important component of seismic design. Among all primary structural components, the vital role of columns in load transfer and redistribution, structural stability, and collapse prevention has been well recognized through observations made in the aftermath of past earthquakes. Numerous analytical, numerical, and experimental studies have been conducted to assess the shear strength of RC columns in the past decades. However, there is still a large scatter (i.e., uncertainty) in the predictions of current empirical and numerical models relative to test data. In this paper, novel data-driven models are presented for predicting the maximum shear strength of rectangular and circular RC columns. To this end, two extensive experimental databases for both types of columns were used in the present study. The data were randomly partitioned into calibration and validation sets. The calibration data sets served as the basis for developing linear and nonlinear equations for predicting the ultimate shear capacity of rectangular and circular RC columns through regression analyses. The Monte Carlo method was employed by conducting 106, 107, and 108 realizations to exhaustively examine the optimal parameter space of the postulated equations. The calibrated predictive models were then validated using the validation data sets; and their performances were also compared to existing models. These validation and comparison studies revealed that a new linear model devised and calibrated in the present study achieved very high accuracy, even compared to various nonlinear models considered. It was, moreover, significantly superior to all prior models in predicting the column shear strengths. This linear model, which is based on physical parameters, can therefore be recommended for engineering practice.
This article, drawn from the National Cooperative Highway Research Program (NCHRP) Synthesis 581: Rehabilitation of Culverts and Buried Storm Drain Pipes, presents current and emerging culvert repair and rehabilitation methodologies, as well as factors affecting their selection and implementation. The synthesis collected and analyzed information from a variety of sources including: a literature review of relevant standards, best practices, and guidance documents; a web-based questionnaire that was completed by 42 state departments of transportation (DOTs); and follow-up interviews to develop case examples. Four major culvert types were examined: corrugated metal, precast concrete three-sided or box structures, precast concrete pipe or arch, and thermoplastic pipe. The survey questionnaire and case examples focused on: culvert types and frequency of their rehabilitation, critical factors affecting the rehabilitation method, local and spot repairs, repair of joints between pipe pieces or metal plates, invert paving and invert lining rehabilitation methods, system-level rehabilitation methods for the entire culvert lining, existing structural capacity, in-house rehabilitation, and quality assurance. This article discusses key findings, spot and joint repair methods, system-level methods, consideration of existing structural capacity, and case examples from various state DOTs.
A new bar slip model is developed to account for the contribution of reinforcement anchorage slip to the total displacement of corroded reinforced concrete (RC) members. An analytical procedure is proposed to model the distribution of the reduced bond stress along the corroded steel bar to predict the reinforcement slip in the anchorage area. The reinforcement slip is formulated using an existing model and by new governing equations defined for different bond regions. The possibility of having an insufficient embedment length is also considered, and a corresponding failure criterion is defined. The bar model is validated by comparing the available data from single bar pullout experiments and an existing bar force-slip model. The proposed column model is implemented using a fiber element model to capture both the monotonic and cyclic behavior of corroded columns. Pseudo-static test data from corroded column specimens are used to validate the proposed column model. Overall, the proposed model captures the slip of a single corroded bar reasonably well to accurately simulate the total lateral displacement of columns with corrosion damage.
Abstract. In this paper, we develop and implement end-to-end deep learning approaches to automatically detect two important types of structural failures, cracks and spalling, of buildings and bridges in extreme events such as major earthquakes. A total of 2,229 images were annotated, and are used to train and validate three newly developed Mask Regional Convolutional Neural Networks (Mask R-CNNs). In addition, three sets of public images for different disasters were used to test the accuracy of these models. For detecting and marking these two types of structural failures, one of proposed methods can achieve an accuracy of 67.6% and 81.1%, respectively, on low- and high-resolution images collected from field investigations. The results demonstrate that it is feasible to use the proposed end-to-end method for automatically locating and segmenting the damage using 2D images which can help human experts in cases of disasters.
This paper presents the results of performance tests of a large number of in-service corrugated metal culverts in Ohio. The test culverts had span lengths varying from 3.4 m (11 ft) to 6.4 m (21 ft) and backfill soil heights over the crown varying from 0.6 m (1.8 ft) to 7.6 m (22.3 ft). Static and dynamic loads were applied by using heavy trucks. The static loads were applied at ten different locations above each culvert. Dynamic load tests were also conducted at six speeds varying from 8 km/h (5 mph) to 64 km/h (40 mph). A portable instrumentation frame was installed inside each test culvert to monitor deflections. Strains on the culvert walls were also measured at fourteen locations using strain gages. Effects of backfill height and loading conditions are investigated. According to the experimental results, a plot of maximum culvert deflection versus backfill height shows a nonlinear relationship. Maximum static load deflections were found to be consistently larger than the maximum dynamic deflections obtained using the same test truck. Deflections are nearly zero for deep culverts with backfill height exceeding 4 m (13 ft). Maximum deflections correlate more closely to AASHTO equivalent line loads than to total truck weight. The data also indicate that culvert behavior is more difficult to predict when backfill heights are shallow because other factors, such as culvert age and condition and soil type, likely play a significant role.
This paper presents the experimental and numerical investigation of the progressive collapse vulnerability of an existing steel building, Haskett Hall, on the Ohio State University campus. The building was tested by removing one of the first-story columns to observe its collapse resistance and to evaluate the effectiveness of current modeling and analysis guidelines. Progressive collapse is a relatively large partial or complete collapse of a structure due to the loss of a vertical load-carrying element—a column in this case. Few researchers have been able to conduct full-scale experiments to understand the progressive collapse mechanism. In this research, deflections and deformations of steel structural components were measured during the field experiment. Computational models and simulations were examined and compared with the experimental data from the field tests. The contribution and effects of infill walls to progressive collapse resistance of frame structures were investigated. The test data collected in this research can be used to help develop recommendations for improved procedures for progressive collapse analysis of frame buildings.
A large number of reinforced concrete buildings collapsed or were heavily damaged during the 7.4 magnitude earthquake that struck northwestern Turkey on August 17, 1999. Recorded peak ground accelerations were relatively low (0.3 g–0.4 g) compared to the magnitude of the structural damage, and the elastic acceleration response spectra from the recorded motions were comparable with the elastic design spectra specified in the current Turkish seismic code. Seismic code requirements are discussed and compared with observed details. Many structural deficiencies were highlighted by the earthquake damage, including: reinforced concrete columns with insufficient confinement and transverse reinforcement, 90-degree hooks at the end of column ties, poor detailing in beam-column joint regions, strong-beam and weak-columns, soft and weak stories, and poor quality construction. Buildings with shear wall structural elements generally performed well.
No abstract is provided for this article.
No abstract is provided for this article.
Column shear failures observed during recent earthquakes and experimental data indicate that shear deformations are typically associated with insufficient transverse reinforcement, low aspect ratio and a few other parameters. It was shown that in some relatively tall columns, shear displacements can be as large as displacements due to flexure and longitudinal bar slip at column ends. However, very few researchers attempted to predict the lateral load-shear displacement relationship. In this paper, a piecewise-linear model is proposed to predict the lateral load-shear displacement relationship. Part of the new model is developed using the analysis results from Modified Compression Field Theory (MCFT). The results from the proposed model, which uses simplified equations, are evaluated and compared with the predictions from existing models as well as column test data. The proposed model is fairly simple, and predicts the lateral load-shear displacement relations relatively accurately at critical stages including shear cracking, peak strength, onset of lateral strength degradation, and loss of axial load carrying capacity.
Behavior of normal strength concrete columns reinforced with a new reinforcement, termed Prefabricated Cage System (PCS) is investigated. A total of 16 small-scale PCS and rebar reinforced column specimens were constructed and tested under monotonic axial displacement. The experimental results indicate that the overall behavior of rebar and PCS reinforced specimens are comparable prior to achieving the peak column load. In general, PCS specimens are more ductile and absorb more energy than similar rebar specimens after the peak load is reached. The effect of different parameters, such as the steel tube thickness, number of longitudinal reinforcements, transverse steel spacing, and crossties on the specimens’ strength and deformation capacity are investigated. A confined concrete model is proposed and used to predict the load–displacement response. The theoretical load–displacement relations obtained from the proposed model are compared with those obtained from the Mander et al. (J Struct Eng 114(8):1804–1826, 1988) confinement model.
The conditional core damage probability (CCDP) of a representative nuclear power plant is estimated for a beyond design basis earthquake (BDBE) using state-of-the-art structural models within a dynamic probabilistic risk assessment (DPRA) framework. Randomness of seismic excitation and uncertainty of structural parameters are considered using a simulation-based approach. Finite element models are developed for the structure and a liquid container (hydro-accumulator), and fluid–structure interaction is considered with the arbitrary Lagrangian-Eulerian method. The CCDP is evaluated through a time-dependent event tree. Also, correlation among multiple hydro-accumulators is investigated. The results show that operator action and implementation time of mobile safety equipment are critical under BDBE in case of loss of offsite power following an earthquake. It was also found necessary to adopt a DPRA approach to determine the available time for action and core damage timing probabilistically.
Progressive collapse can be defined as a chain reaction of failure initiated by loss of one or a few supporting elements due to manmade or natural hazards. As a result of increasing catastrophic events in recent years, the prevention of progressive collapse is increasingly becoming a requirement in building design and analysis. Many approaches have been proposed to prevent or minimize the risk of progressive collapse in new or existing buildings. Among a number of building codes, standards and design guidelines for progressive collapse, General Services Administration (GSA, [2]) and Department of Defense (DoD, [3]) address progressive collapse mitigation explicitly. They provide quantifiable and enforceable procedures to resist progressive collapse. Over the last decade, extensive studies have been performed to improve the design of buildings against progressive collapse by modifying the design codes, as well as to evaluate the progressive collapse potential of existing or new buildings by computer modelling and experiments. Very limited or no research, however, has been carried out by physically testing an actual full-scale steel building for the progressive collapse analysis. In this study, progressive collapse performance of two existing buildings was investigated through both experimental testing and computational analysis. Each building was tested by physically removing four first story perimeter columns prior to building's scheduled demolition to simulate the sudden column removals that leads to progressive collapse. Progressive collapse resistance of each building was investigated using the commercially available computer program, SAP2000 [4], and following the GSA guidelines. Two different analysis procedures were evaluated for their effectiveness in modeling progressive collapse scenarios; linear static and nonlinear dynamic procedures. Two- and three-dimensional models of steel frame buildings were developed to analyze the progressive collapse response. Differences and implications of each model and analysis are discussed. The strain values recorded in the field were compared with the results from a computer model of each building. It was expected that the field experiments and analytical studies can provide both practical and fundamental information on the collapse response of an existing building with a regular structural configuration.
In this paper, a new framework is proposed for monitoring the dynamic performance of bridges using three different camera placements and a few visual data processing techniques at low cost and high efficiency. A deep learning method validated by an optical flow approach for motion tracking is included in the framework. To verify it, videos taken by stationary cameras of two shaking table tests were processed at first. Then, the vibrations of six pedestrian bridges were measured using structure-mounted, remote, and drone-mounted cameras, respectively. Two techniques, displacement and frequency subtractions, are applied to remove systematic motions of cameras and to capture the natural frequencies of the tested structures. Measurements on these bridges were compared with the data from wireless accelerometers and structural analysis. Influences of critical parameters for camera setting and data processing, such as video frame rates, data window size, and data sampling rates, were also studied carefully. The research results show that the vibrations and frequencies of structures on the shaking tables and existing bridges can be captured accurately with the proposed framework. These camera placements and data processing techniques can be successfully used for monitoring their dynamic performance.
Very limited full-scale experiments have been conducted to understand the mechanism of progressive collapse, which involves partial or complete collapse of a structure typically due to the loss of a vertical load carrying element(s). Progressive collapse design guidelines recommend simplified analysis procedures involving instantaneous removal of specified critical columns in a building. This research investigates the effectiveness of such commonly used methodologies by testing the vulnerability of an existing steel building on the Ohio State University campus. One first-story column was removed from the building to understand how the loads are redistributed. Deflections and strains within the neighboring beams and columns were measured during column removal. Experimental data from the field test were compared with data from structural analysis. The main conclusion is that more than 70% of the loads applied on the removed column are redistributed within the perimeter frame; the remaining loads are carried by the interior columns after the column is removed.
Probabilistic risk assessment of nuclear power plants initially focused on events initiated by internal faults at the plant, rather than external hazards including earthquakes and flooding. Although the importance of external hazards risk analysis is now well recognized, the methods for analyzing low probability external hazards rely heavily on subjective judgment of specialists, often resulting in substantial conservatism. This research developed a framework to integrate the risk of seismic and flooding events using realistic structural models and simulation of response of nuclear structures. The results of four application case studies are presented.
Two- and three-dimensional macrotexture characteristics of various surfaces were measured using five different testing methods including sand patch method, laser profiler, laser texture scanner, circular texture meter, and x-ray computed tomography (CT) scanning. A dynamic friction tester was also used to measure the friction resistance of the same surfaces. Asphalt and Portland cement concrete samples of various mix designs and finishes and other commonly manufactured textured samples were used. Relationship between the macrotexture and friction was investigated. Mean texture depth (MTD) of 26 laboratory specimens was obtained from volumetric sand patch tests. Two-dimensional profiles and mean profile depth (MPD) of specimens were measured by a laser profiler. A laser texture scanner and a circular texture meter were also used to calculate the MPD of sample surfaces. Three-dimensional rendering of the surfaces were obtained from laser texture scanner and x-ray CT scans. Using the experimental data collected in this study, relationships between friction resistance and macrotexture obtained from different methods were investigated. The estimated texture depths predicted from laser profiler, laser texture scanner, and CT meter were comparable to the MTD obtained from sand patch tests. Also, the friction resistance increased with increasing surface macrotexture.
