Cascadia Lifelines Program Webinar Series

This webinar will be Dylan Sanderson's MS thesis defense presentation on the development of a methodology to deaggregate the results of a multi-hazard damage analysis by extending the traditional multi-hazard damage analysis to consider both population characteristics and independent hazards. The methodology is applied to the joint seismic-tsunami hazard at Seaside, Oregon, considering four infrastructure systems: (1) buildings, (2) transportation network, (3) electric power network and (4) water supply network. Damages to all infrastructure systems are evaluated, and the networked infrastructures are used to inform parcel connectivity to critical facilities. US Census data and a probabilistic housing unit allocation method are implemented to assign detailed household demographic characteristics at the parcel level. Six dimensions of deaggregation are introduced: (1) spatial, (2) hazard type, (3) hazard intensity, (4) infrastructure system, (5) infrastructure component, and (6) housing unit characteristics. The damages, economic losses and risks, and connectivity to critical facilities are deaggregated across these six dimensions. The results show that deaggregated economic loss and risk plots can allow community resilience planners the ability to isolate high-risk events, as well as provide insights into the underlying driving forces. Geospatial representation of the results allows for the identification of both vulnerable buildings and areas within a community and is highlighted by the spatial pattern of parcel disconnection from critical facilities. The incorporation of population characteristics provides an understanding of how hazards disproportionately impact population subgroups and can aide in equitable resilience planning.

This webinar is being offered by IRIS Gage/Sage webinar series. Important infrastructure such as highways in the Pacific Northwest traverse particularly unstable terrain throughout much of the state, resulting in maintenance, system unreliability due to frequent closures and restrictions, and safety hazards due to landslides and rockfalls. Seismic activity significantly amplifies these negative economic and community impacts. This presentation will discuss efficient data processing strategies to utilize point cloud data to analyze rockfall activity at rock outcrops from repeat lidar or Uncrewed Aircraft Systems (UAS) Structure from Motion/MultiView Stereo (SfM/MVS) photogrammetric surveys that enable one to simultaneously look closely at detailed features on the slope as well as from afar to evaluate an entire corridor. These technologies enable personnel to safely capture data for active rock slopes that may be otherwise inaccessible. Nevertheless, the “Big Data” generated through these technologies combined with other data sources provide immense challenges in terms of acquisition and data processing. This presentation will discuss a suite of tools enabling efficient analyses of detailed remote sensing data to quantify and visually communicate rockfall hazards. These tools include efficient surface modeling algorithms, rockfall cluster detection to produce magnitude-frequency relationships, the Rockfall Activity Index-a morphological-based assessment technique, and seismically-induced rockfall debris estimates. Such approaches yield many important safety benefits, enable mitigation of geohazards before catastrophic events occur, and improved responses after major seismic events.

This webinar is part of the OSU College of Engineering Webinar Series. Failure to mitigate impacts of climate change and adapt to related stresses, extreme events (such as floods, droughts, and storms), and natural hazards have been identified as the most likely global risks by World Economic Forum in a recent 2020 report. A collective will is critical to tackling these risks. But how do we mobilize a collective problem-solving process in communities for identifying opportunities to build resilience to climate change and adapt to learned lessons? In this presentation, we will examine whether a collaboration between humans and machines could create new ways for communities to create solutions for this intractable problem. We will also explore what such a collaboration might look like in watershed communities prone to flooding.

This presentation presents the use of controlled blasting as a source of seismic energy to obtain the coupled, dynamic, linear-elastic to nonlinear-inelastic response of a plastic silt deposit at the Port of Portland. The experimental program, instrumentation, and subsurface investigation is described, including laboratory investigations on intact specimens for comparison to the in-situ response. Characterization of blast-induced ground motions revealed that the maximum particle displacements, shear strain, and corresponding residual excess pore pressures developed in the silt deposit are associated with the low frequency near- and far-field shear waves that are within the range of earthquake frequencies, whereas the higher frequency compressive P-wave did not produce residual excess pore pressure. Three blasting programs conducted at the test sites were used to develop the initial and pre-strained relationships between shear strain, excess pore pressure, and nonlinear shear modulus degradation, revealing the initial threshold shear strain to initiate soil nonlinearity and to trigger generation of residual excess pore pressure ranging from 0.002 to 0.003% and 0.008 to 0.012%, respectively, where the latter corresponded to a reduction of the maximum shear modulus of approximately 30%. Drainage and excess pore pressure migration appears to have contributed to a stiffer large-strain response than otherwise expected from laboratory-derived shear modulus reduction curves Following pre-straining and dissipation of excess pore pressures within the silt deposit, the shear strain necessary to trigger residual excess pore pressure increased two-fold. Greater excess pore pressures were observed in-situ compared to that of intact direct simple shear (DSS) test specimens at a given shear strain amplitude. The reduction of in-situ undrained shear strength within the blast-induced excess pore pressure field measured using vane shear tests compared favorably with that of DSS test specimens.

This presentation will discuss research OSU is doing for NIST related to community resilience.

The electrical power system faces threats both natural and man-made. This presentation will present background and research at OSU on electrical system resilience to earthquakes and cyber attacks, including potential costs, impacts, and strategies for mitigation.

The NHERI Natural Hazards Reconnaissance Facility (referred to as the “RAPID Facility"), headquartered at the University of Washington (UW), is a collaboration between UW, Oregon State University, Virginia Tech, and the University of Florida. The facility enables the natural hazards and disaster research communities to conduct next-generation rapid response investigations to characterize civil infrastructure performance and community response to natural hazards, evaluate the effectiveness of design methodologies, calibrate simulation models, and develop solutions for resilient communities. The facility engages in a range of activities including: (1) acquiring, maintaining, and operating state-of-the-art data collection equipment, (2) developing and supporting mobile applications for interdisciplinary field reconnaissance, (3) providing advisory services and basic equipment logistics support for research investigations, (4) facilitating the systematic archiving, processing and visualization of acquired data in DesignSafe-CI, (5) training a broad user base through workshops and other activities, and (6) engaging the public by facilitating citizen science initiatives, as well as through community outreach and education.