Mike Dupuis

Architectural features and other irregularities in the gravity system which apply gravity-induced lateral demands to the seismic force resisting system are being incorporated in new buildings. These gravity-induced demands have raised concerns due to the perceived potential for a ratcheting effect to occur during seismic loading. This paper summarizes the results of a study to identify if there are behavioral trends not recognized within the scope of current building codes. To this end, a nonlinear, parametric study was conducted in OpenSees to investigate the inelastic response of concrete shear wall buildings with a range of design characteristics, including gravity-induced lateral demands. The results demonstrated that a seismic ratcheting effect can develop and amplify inelastic displacement demands. The effect is significantly more prevalent in coupled shear walls compared with cantilevered shear walls. An irregularity class to address buildings with gravity-induced lateral demands on the seismic force resisting system is proposed for the 2015 National Building Code of Canada.

High-quality earthquake ground-motion records are required for various applications in engineering and seismology; however, quality assessment of ground-motion records is time-consuming if done manually and poorly handled by automation with conventional mathematical functions. Machine learning is well suited to this problem, and a supervised deep-learning-based model was developed to estimate the quality of all types of ground-motion records through training on 1096 example records from earthquakes in New Zealand, which is an active tectonic environment with crustal and subduction earthquakes. The model estimates a quality and minimum usable frequency for each record component and can handle one-, two-, or three-component records. The estimations were found to match manually labeled test data well, and the model was able to accurately replicate manual quality classifications from other published studies based on the requirements of three different engineering applications. The component-level quality and minimum usable frequency estimations provide flexibility to assess record quality based on diverse requirements and make the model useful for a range of potential applications. We apply the model to enable automated record classification for 43,398 ground motions from GeoNet as part of the development of a new curated ground-motion database for New Zealand.

Annual rates of failure which consider the effect of dam type, construction era, and dam age were estimated for dams in the United States by examining the National Inventory of Dams and the Worldwide Historical Dam Failures Database. Based on information from these databases, there has been a total of 5,628,516 dam-years (sum of years in service for all dams), 2,694 dam failures, and thus 0.00048 dam failures per dam-year. Concrete and earthfill dams both have less than 0.0005 failures per dam-year; masonry and rockfill dams have more than 0.001 failures per dam-year and timber dams have more than 0.0035 failures per dam-year. For all dam types, failures per dam-year are greatest in the first five years after construction and steadily decrease with increasing dam age except for earthfill and rockfill dams. Earthfill and rockfill dams reach the lowest rates of failures per dam-year when they are between 20-50 years old with an increase in failure rate, especially for earthfill dams, after 50 years after construction. Results from this study are predicated by the available data, which likely does not include information for all dams or dam failures.

Detailed design packages are required to ensure that structural components of concrete dams satisfy applicable design guidelines. These design packages are important for the design and analysis of appurtenant dam structures—such as concrete anchors, spillway and powerhouse slabs, retaining and training walls, powerhouse beams, and foundations—because they are the primary record of design and capacity checks by the engineer of record. However, these design checks are tedious and time consuming to complete, especially for unique one-off structural elements which are common for dams. Furthermore, project changes can require multiple iterations of a design concept which can result in repetition of these design checks prior to final design. Commercially available software programs are available for structural design checks, and partially address this problem; however, these programs suffer from three main shortcomings: (i) lack of an application programing interface limits the ability to rapid prototype design alternatives, (ii) awkward compilation of multiple structural components into well-organized project design documents, and (iii) trial student licences have limited durations and full licenses are not freely available. To address these shortcomings, I have developed a freely available educational software program which can be used as either a graphical user interface or as an application programming interface. The stand-alone graphical user interface requires no programming knowledge and can be run from a downloaded executable file. The application programming interface can be accessed as a Python module and provides additional power for engineers knowledgeable in Python to interact with the software directly through their own Python scripts. The software is provided for educational use only with the hope that it will motivate companies and organizations within the hydropower industry to develop similar technologies.

High-quality large-magnitude subduction earthquake ground-motion records are needed as inputs for response history analysis of dams in regions adjacent to the Cascadia Subduction Zone. Quality assessment of candidate ground-motion records is time consuming if done manually and poorly handled by automation with conventional mathematical functions; therefore, a supervised deep-learning-based model was developed in a previous study to estimate the quality and minimum usable frequency of ground-motion records through training on 1,096 records from earthquakes in New Zealand, which is an active tectonic environment with crustal and subduction earthquakes. In that study, the model was found to perform well for small-to-moderate magnitude earthquake records from active shallow crustal, subduction slab, and subduction interface earthquakes; however, the model’s performance for large-magnitude earthquake records was not investigated. In this study, we evaluate the performance of the model for assessment of records from the 2010 M8.8 Maule and 2011 M9.1 Tohoku subduction interface earthquakes. We utilize high-quality processed subduction records and then superimpose various amplitudes of artificial background noise to degrade quality and then apply the model quality for quality classification. Eleven high-quality ground-motion records were selected based on the model results and then linearly scaled to a target spectral acceleration for a hypothetical site in British Columbia to produce a suite of large-magnitude subduction interface earthquake ground-motions suitable for structural response history analysis.