cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17603/ds2-fvgg-9h66
title: Natural Hazards Research Summit 2022: Multi-Directional Cyber-Physical Experimental Testing to Establish Multi-natural Hazard Resiliency of Structural Systems and Building Content Hazard Mitigation

description: Protecting both the essential building contents and the structural system—as well as facilitating and accelerating the post-event functionality of business operations—is a major concern during natural hazards. Floor isolation systems (FIS) with rolling pendulum bearings along with nonlinear fluid viscous dampers (NFVD) have been proposed to mitigate damage and enhance the resiliency of non-structural and structural systems, respectively. These devices are designed to decrease vibrations under dynamic loading conditions. In this poster, we introduce research using tridimensional nonlinear cyber-physical experimental testing (i.e., real-time hybrid simulations) to validate the performance of these response modification devices placed in structural systems under wind and earthquake loading conditions. The effects of soil-structure-foundation and fluid-structure interactions were also accounted for. The novelty of the project is the use of multi-directional large-scale real-time hybrid simulations of complex nonlinear systems under wind and earthquake demands to combine experimental structural modification passive devices with analytical multi-story buildings considering soil-foundation interaction via neural network. Results show that the FIS and NFVD can significantly reduce the demand on non-structural and structural systems of buildings subjected to natural hazards whose response can be also significantly affected by soil-foundation-structure interaction. A product of this research is the data (which is linked in Related Works), which can be used to compare with new studies using the same experimental techniques and structural modification devices or with alternative approaches. Researchers interested in multi-natural hazards resilience and mitigation, state-of-the-art structural experimental techniques, and the use of machine learning as a tool to improve modeling efficiency will benefit from its results. Also, companies dedicated to the commercial development of structural response modification devices, as well as policymakers working or with interest in economic and social resilience.
DOI: 10.17603/ds2-ga7q-3j10
title: A Nationwide Analysis of Community-Level Floodplain Development Outcomes and Key Influences

description: Development patterns and climate change are contributing to increasing flood risk across the United States. Limiting development in floodplains mitigates risk by reducing the assets and population exposed to flooding. Here, we develop two indexes measuring floodplain development for 18,548 communities across the continental United States. We combine land use, impervious surface, and housing data with regulatory flood maps to determine what proportion of new development has taken place in the floodplain. Nationwide from 2001 to 2019, 2.1 million acres of floodplain land were developed, and 844,000 residential properties were built in the floodplain. However, contrary to conventional perceptions of rampant floodplain development, just 26% of communities nationwide have developed in floodplains more than would be expected given the hazard they face. The indexes and the analyses they enable can help guide targeted interventions to improve flood risk management, to explore underlying drivers of flood exposure, and to inform how local-to-federal policy choices can be leveraged to limit hazardous development.
DOI: 10.17603/ds2-rn6t-xq10
title: Research Experiences for Undergraduates (REU), NSF NHERI 2024: Assessment of Fire Sprinkler System in a 10-Story Cold-Formed Steel Building During Seismic Loading Scenarios

description: Fire sprinkler systems are pivotal to saving lives and reducing building damage caused by after-earthquake fires. Fire sprinkler (FS) systems can better withstand seismic forces through the utilization of fire sprinkler codes, building codes, and numerical models to aid in the design layout and overall to improve seismic performance. The data that the fire sprinkler model produced will be reused to construct an instrumentation during seismic loading scenarios of the 10-story CFS building. The unique response of high-rise CFS buildings under seismic loading conditions have not been researched and neither have the performance of fire sprinkler systems within these experimental buildings. Further research of a FS system's response in a high-rise CFS building needs to be investigated as their is a research gap. The audience in question are for researchers to further understand how non-structural systems interact with experimental structural systems.
DOI: 10.17603/ds2-smvn-1f34
title: Natural Hazards Research Summit 2024: Data-Driven Telecommunication Outage Prediction During Hurricane Events

description: This poster describes a data-driven approach to predict county-level telecommunication outages during hurricane events.
DOI: 10.17603/ds2-wz53-4660
title: SCNet: A Multi-attribute Data Set for Seismic Collapse Behavior of Deep Steel Wide-Flange Columns
title: in Prediction of Seismic Collapse Behavior of Deep Steel Wide-Flange Columns Using Machine Learning Methods

description: In this project, we explore the efficiency of different machine learning (ML) methods in predicting the seismic collapse behavior of steel deep wide flange (W-shape) columns. Steel Column Net (SCNet), a database of  more than nine hundred deep W-shape columns subjected to combined axial and lateral loads is collected and compiled. The efficiency of five ML classification models is explored to identify the failure modes of columns in a randomly assigned test set from SCNet. Whereas, the efficiency of four ML regression models is explored to predict the cumulative inelastic rotation of columns in a randomly assigned test set from SCNet.
description: Steel Column Net (SCNet), a dataset of more than nine hundred experimental and numerical results of deep W-shape columns with different attributes is assembled and compiled. Three failure modes are distinguished in SCNet: local, global, and coupled modes while column rotation capacity is expressed in terms of its cumulative inelastic rotation until failure.
DOI: 10.17603/ds2-yry6-r324
title: Hurricane Harvey
title: in Analysis of tweets posted by professional sources of weather forecast and warning information during tropical cyclone events

description: This project collected, filtered, and analyzed tweets from professional sources of meteorological information (including the National Weather Service, broadcast meteorologists, and emergency managers) during several tropical cyclone events. Here, we share documentation for our Twitter data collection, coding, and filtering processes, as applied to these tropical cyclone cases. The documentation shared here allows users to take “big data” from social media and filter it in order to yield smaller, targeted datasets of the most interest to at-risk users during disasters.
description: The documentation provided here describes our Twitter data coding and filtering schemes used to analyze professional source Twitter activity during Hurricane Harvey. The analysis focused on understanding the dissemination and retransmission of different kinds of information provided by a wide variety of professional sources in the Houston metropolitan area. For this analysis, we used data collected by our colleagues at the University of Colorado - Boulder as described by Bica et al. (2019).

The authors thank Julie Demuth and Melissa Bica for their collaboration on the project that included development and use of these coding schemes.
DOI: 10.17603/ds2-21k1-sj54
title: Topobathymetric Digital Elevation Model (DEM) for Flood Modeling in Harris County, TX

description: A Digital Elevation Model (DEM) that combines both topobathymetry data for 2D flood modeling in Harris County, TX. We incorporate channel bathymetry from over 36 river models (e.g., HECRAS) for major rivers and tributaries across multiple HUC10 watersheds.
DOI: 10.17603/ds2-5ee0-dw76
title: ArchImageLib: libraries of annotated and unannotated image data of masonry railway bridges and viaducts
title: in Automating inspection and damage classification of ageing masonry railway bridges and viaducts 

description: This 'ArchImageLib' dataset contains image data for 13 masonry arch railway bridges and viaducts in the UK. Overall, it includes 44 surveyed arch spans and a total surface area of masonry of approximately 15,300 square meters. A subset of the images has been processed to generate annotations, capturing mortar joints and damage including cracking, spalling, mortar loss, and vegetation. These bridges and viaducts present in a range of structural conditions, and the dataset therefore presents a valuable resource for the training and validation of algorithms for automated inspection and damage classification. Given the increasing threats to ageing masonry infrastructure from extreme loading, including climate-driven wind and flood loading, the development of such algorithms is critical to safeguarding these assets for future generations.
DOI: 10.17603/ds2-f11m-d683
title: Experimental and numerical modeling of structure-soil-structure interaction on liquefiable soils and effects of mitigation in urban settings

description: This research integrates experimental and numerical methods in geotechnical and structural engineering to investigate the behavior of nonlinear, similar and dissimilar buildings on liquefiable soils in the context of building performance. In this part of the project, we performed a series of centrifuge tests to investigate the influence of the liquefaction mitigation techniques on the seismic site response and performance of the SFS (soil-foundation-structure) system on a layered, liquefiable deposit. Later, the role of building properties and spacing as well as the thickness of the liquefiable layer on system performance are explored via a limited number of 3D finite element simulations. The insight from this study aims to guide future research on the role of SSSI on liquefiable deposits and development of design recommendations.
DOI: 10.17603/ds2-hsqp-k357
title: Replication Data for "Vulnerability in a Tropical Cyclone Risk Model: Philippines Case Study"

description: This dataset produces a tropical cyclone risk (e.g. asset loss) model for the Philippines based on open-source data, geared at supporting nonprofit applications. This model is appropriate for estimating return levels of tropical cyclone wind speeds and asset losses at the regional to national scale in the Philippines. The files and code included in this data repository allow for reproduction of the different model components (e.g. the hazard, vulnerability, and exposure layers) and the model validation. The data produced by this model and used in the publication are also made available here-- namely the tropical cyclone wind fields for observed and synthetic storms over the Philippines, the vulnerability and exposure layers, and the resultant asset losses. If you wish to run the code, please first follow instructions in the README to set up the necessary environment and functions.
DOI: 10.17603/ds2-1fka-8y31
title: Undergraduate Research Experience (REU), NHERI 2019: Limitations of Multi-channel Analysis of Surface Waves (MASW) Method on Subsurface Anomaly Detection

description: This project focuses on understanding the limitations of a promising non-invasive form of soil profiling called Multi-channel Analysis of Surface Wave (MASW) Method. Work was done on a python script to optimize the processing phase of this MASW method powered by the use of DENISE on TACC computers.
DOI: 10.17603/ds2-2117-1565
title: StEER - 17 June, 2019 Yibin City, Sichuan, China Earthquake: Event Briefing

description: This Event Briefing (1) summarizes the seismic characteristics of the 17 June 2019 Yibin City, Sichuan, China earthquake, (2) overviews damage to buildings and other infrastructure, as well as disruption to the community in terms of downtime and economic losses, (3) presents city-scale computational simulations generated shortly after the earthquake, and (4) summarizes key lessons learned. Information provided herein was gathered from various websites, news channels, and computational simulations. Therefore, this briefing does not include insights from detailed field investigations.
DOI: 10.17603/ds2-5ysj-a554
title: One-year Post-tornado Repair Progress: Wave 3
title: in StEER - 28 MAY 2019 LINWOOD, KS EF4 TORNADO: FIELD ASSESSMENT STRUCTURAL TEAM 1 (FAST-1)

description: On May 28, 2019, a destructive EF4 tornado struck north-eastern Kansas, resulting in severe damage in Leavenworth County and surrounding areas. The tornado travelled 31.8 miles in 55 minutes and had a maximum width of one mile. There were 18 injuries but no fatalities. The Structural Extreme Events Reconnaissance (StEER) funded a quick response field study, referred to here as Wave 1, to document post-tornado damage to building structures along the tornado path. The Wave 1 survey documented initial building damage, aerial imagery of the tornado path and provides an essential baseline for subsequent impact and recovery studies. A second and third wave of data collection were funded by PI Sutley’s fellowship funding from the National Academies of Science, Engineering, and Medicine Gulf Research Program, and were executed six months and twelve months after the tornado, respectively. The Wave 2 and 3 teams consisted of structural engineering professors and students, behavioral economics professor and students, and public administration and urban planning students from the University of Kansas. Goals for Wave 2 and Wave 3 were to: (1) document risk perception, sheltering behavior, impact, and recovery experience of households during and since the May 2019 tornado, and (2) document the repair progress for homes along the tornado path six and twelve months after a major tornado in rural Kansas. This project achieves collected data from Waves 1, 2, and 3. This collection also archives survey instruments and Institutional Review Board protocol approved by the University of Kansas IRB office for Waves 2 and 3.
description: This mission achieved the human subject research protocols, data collection instruments, and data for the physical repair progress for homes along the tornado path twelve months after the 2019 EF4 Linwood, Kansas tornado. 144 residential buildings were assessed in Wave 2. Only and all of the 27 unrepaired homes and 28 homes with repairs in progress recorded in Wave 2a were assessed in Wave 3 for continued repair progress.
DOI: 10.17603/ds2-6k4n-bn46
title: Household Survey Instrument, 2010: Wave 2
title: in Galveston Recovery from 2008 Hurricane Ike - A “Living Laboratory” for Examining Community Recovery and Resilience After Disaster

description: This collection archives instruments and planning materials related to the household survey for Wave 2 of the Galveston, TX Field Study conducted by the Hazard Reduction Recovery Center, as part of a National Science Foundation-funded project. The instrument was designed to gather specific types of information on the household (social) that occupied the housing unit at the time of the flooding. The survey instrument was designed to collect information on: (1) dislocation and reoccupancy of household members with basic information, (2) repair and rebuilding, (3) applications to disaster assistance programs (insurance, FEMA, SBA), (4) losses and sources of assistance, (5) mitigation behavior, (6) changes in jobs/employment, (7) health-related service use, (8) neighborhood and quality of life, and (9) additional household socioeconomic and demographics (e.g., highest education status, race/ethnicity, and annual income). The survey was designed to be conducted in-person. Based on the Wave 1 and Wave 2 household data, the center established a three-year period of panel studies of households and housing units to track recovery trajectories and adaptive learning.
description: Researchers from the Hazard Reduction & Recovery Center (HRRC) at Texas A&M University have created a living laboratory for community resilience in Galveston, Texas, allowing them to identify previously untested relationships between the physical and social, and economic development patterns in physically vulnerable communities. With funding from the NSF, Dr. Van Zandt and her team at Texas A&M University collected primary data in the months immediately after Galveston Island and Bolivar Peninsula were struck by Hurricane Ike in September 2008, and again about a year later and two years later.
Data was collected from physical assessment of 1500 households. Household surveys were completed for 570 of those households, for a response rate of 38 percent. Business surveys were completed for 287 businesses in Galveston County (including areas on the Island and on the mainland). These data were (and continue to be) used to test hypotheses related to the resiliency and recovery of communities after a natural disaster. We here publish the instruments used to gather the data. The original data is not publicly available due to Institutional Review Board (IRB) restrictions in place at the time of collection. For further questions about the original data you may contact the HRRC at Texas A&M.
DOI: 10.17603/ds2-a06x-f358
title: Door-to-Door Damage Assessment Survey: Wave 1
title: in StEER - 28 MAY 2019 LINWOOD, KS EF4 TORNADO: FIELD ASSESSMENT STRUCTURAL TEAM 1 (FAST-1)

description: On May 28, 2019, a destructive EF4 tornado struck north-eastern Kansas, resulting in severe damage in Leavenworth County and surrounding areas. The tornado travelled 31.8 miles in 55 minutes and had a maximum width of one mile. There were 18 injuries but no fatalities. The Structural Extreme Events Reconnaissance (StEER) funded a quick response field study, referred to here as Wave 1, to document post-tornado damage to building structures along the tornado path. The Wave 1 survey documented initial building damage, aerial imagery of the tornado path and provides an essential baseline for subsequent impact and recovery studies. A second and third wave of data collection were funded by PI Sutley’s fellowship funding from the National Academies of Science, Engineering, and Medicine Gulf Research Program, and were executed six months and twelve months after the tornado, respectively. The Wave 2 and 3 teams consisted of structural engineering professors and students, behavioral economics professor and students, and public administration and urban planning students from the University of Kansas. Goals for Wave 2 and Wave 3 were to: (1) document risk perception, sheltering behavior, impact, and recovery experience of households during and since the May 2019 tornado, and (2) document the repair progress for homes along the tornado path six and twelve months after a major tornado in rural Kansas. This project achieves collected data from Waves 1, 2, and 3. This collection also archives survey instruments and Institutional Review Board protocol approved by the University of Kansas IRB office for Waves 2 and 3.
description: This mission contains a quick response field study, referred to here as Wave 1, to document post-tornado damage to building structures along the tornado path. The Wave 1 survey documented initial building damage, aerial imagery of the tornado path and provides an essential baseline for subsequent impact and recovery studies. 271 building structures were assessed for physical damage caused by tornado hazards using the StEER structural wind damage rating survey.
DOI: 10.17603/ds2-e73f-j037
title: Grooved Plate Experiments
title: in Collaborative Research: Simulating Crack Propagation in Steel Structures Under Ultra-Low Cycle Fatigue and Low-Triaxiality Loading from Earthquakes and Other Hazards

description: Experimental test data from this project has been used to develop, calibrate and validate computational models to simulate ductile crack initiation and propagation in steel structures under ultra-low cycle fatigues.  The resulting models can be used in fundamental and applied research to evaluate earthquake-induced fracture limit states in steel structures.  The experimental test data can be used by researchers to calibrate and validate alternate computational models, which they have developed.
description: Monotonic testing of grooved plate specimens for calibration of fracture model parameters.
DOI: 10.17603/ds2-eppg-5133
title: RC column backbone curve dataset

description: This dataset provides more than 100 backbone curves of reinforced concrete columns that are collected from Chinese literature. The data could be used in structural engineering or earthquake engineering. The details of the specimens can be found in the spreadsheet and the backbone curves are available in the csv files. The first three rows of each csv file contain the author, the publishing year, the name and the number of force-displacement pairs of the specimen. From the fourth row onwards, the force-displacement pairs are provided in adjacent columns. The first column contains the top-displacement values (in mm), and the second column contains the lateral-load values (in kN). Regardless of the actual test configuration, all force-displacement data are reported in terms of an equivalent cantilever column.
DOI: 10.17603/ds2-fnat-6024
title: Southern California Basin and Non-Basin Classification Algorithm for Ground Motion Site Amplification Model Applications

description: This project presents a model and dataset that complements the study carried out to propose a statistical classification model that determines the probability of a location residing within or outside a basin based on simple geologic features such as ground surface texture.