cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17603/ds2-3zdj-4937
title: Machine Learning Models for the Evaluation of the Lateral Spreading Hazard in the Avon River Area Following the 2011 Christchurch Earthquake

description: This project contains a Jupyter Notebook and python codes to run a suite of machine learning Random Forest Classifier algorithms to predict liquefaction induced lateral spreading displacement. This study is trained using data from the 2011 Christchurch earthquake in the Avon River area. The trained models can be used in the range of applicability reported in the ReadMe file. The Jupyter Notebook example files can be adapted to train any dataset. All the information are contained in the ReadMe file.
DOI: 10.17603/ds2-9cxw-kq20
title: Cyclic Direct Simple Shear Tests - Ottawa F50
title: in Direct Simple Shear Testing on Ottawa F50 and F65 Sand

description: Pretriggering, triggering, and post-triggering response of Ottawa F50 sand
description: This project summarizes the results of undrained cyclic direct simple shear (DSS) tests performed on specimens of Ottawa F50 and F65 sand. Experiments were conducted using the GEOTAC Direct Simple Shear testing system available in the Soil Interactions Laboratory at the University of California, Davis. Data are summarized as liquefaction triggering curves (Cyclic Stress Ratio versus Number of Cycles) and as stress strain loops, stress paths, vertical stress versus shear strain, and vertical compliance versus shear strain.The data available is the raw data (without any post-processing or filtering) for all the experiments illustrated in the report.
DOI: 10.17603/ds2-xc9j-3054
title: How are U.S. Cities Planning for Heat?

description: The aim of this project is to determine the prevalence and nature of urban heat management goals and interventions in municipal planning documents. To do this, a research team comprised of students and faculty at UCLA and Arizona State University developed a database of 175 adopted plans from the 50 most populous cities in the United States. Each document was then scanned for references to 50 original heat content variables and 25 secondary social and environmental variables pertaining to heat. Heat-specific clauses were coded for heat framings, hard and soft interventions, references to equity, and data sources. The occurrence and frequency of the heat content variables in each plan are available at the clause and plan scale and all variables are available at the city scale.
DOI: 10.17603/ds2-z443-jb24
title: Phase II - Modified designs
title: in University of Auckland Lightly Reinforced Concrete Wall Tests

description: A series of experimental tests of large-scale lightly reinforced concrete walls were conducted at the University of Auckland.  The test were used to investigate minimum vertical reinforcement provisions and formed the basis for revisions to the New Zealand Concrete Structures Standard (NZS 3101:2006 (A3)) and the US Building Code Requirements for Structural Concrete (ACI 318-19). This dataset summarizes the results from the 11 tested walls including all sensor data (load cell, LVDT, string-pot displacement gauge, displacement transducer and strain gauge). Detailed instrumentation plan, loading protocol, test sequences, test observations and photos that were taken throughout the testing are also provided.  The dataset is intended to serve as a reference for future work, as well as an open resource to be used in future research.
description: Five reinforced concrete walls designed with modified minimum vertical reinforcement in accordance with NZS 3101:2006 (Amendment 3)
DOI: 10.17603/ds2-zwg3-nv98
title: Evaluating the performance of historic masonry in Mayfield after the 2021 tornado

description: This data was curated for the damaged buidlings in Mayfield. The data was completed using the streetview images, unmanned aerial vehicle images and inspector note to fill the missing blanks.
DOI: 10.17603/ds2-05s8-ah21
title: 2021 Hurricane Henri predictive and post-storm survey instruments
title: in Public longitudinal panel surveys collected during and after hazardous weather threats: Hurricanes

description: These two survey instruments were developed and used to collect longitudinal panel survey data (i.e., repeated surveys of the same people) for Hurricane Henri in 2021. The predictive waves survey instrument was rapidly deployed and fielded three times over the course of a few days as the hurricane was threatening and approaching landfall. Each wave was fielded for approximately 13 to 19 hours with an 8- to 19-hour interval in between. The post-storm wave survey instrument was fielded one time after the hurricane dissipated. It was fielded 5 days after the final predictive survey wave, and it was fielded for 12 days.
description: These are novel datasets of longitudinal panel survey data (i.e., repeated surveys of the same people) when a hurricane is threatening and approaching landfall in the mainland U.S. and after the hurricane has dissipated. Three survey waves were collected pre-landfall when the hurricane was threatening (the threat / predictive phase), and one survey wave was collected post-storm (post landfall or dissipation). The three waves of data collected during the predictive phase measured what forecast and other risk information respondents were getting, respondents' risk perceptions, and respondents' protective behavioral responses, all pertaining to the hurricane risks at that time. The data collected during the post-storm wave correspondingly measured what forecast and other risk information was most useful and what people's actual experiences were with the hurricane. Such rapidly deployed, event-based, repeated-measure data for hurricanes are novel. This project includes datasets for the following hurricane events: Hurricanes Laura and Marco in 2020, Hurricane Henri in 2021, and Hurricane Ian in 2022.
DOI: 10.17603/ds2-m3b2-re28
title: A Case Study for Modeling Interdependencies Between the Building Portfolio, Transportation Network, and Healthcare System in the Community

description: A multi-system model is proposed to simulate the interaction between the building portfolio, transportation network, and healthcare system of an earthquake-stricken community. The proposed simulation model and its capabilities are demonstrated through a case study that focuses on modeling the seismic resilience of a part of Shelby County, Tennessee. The building portfolio data was extracted from the database provided in Ergo-EQ software version 4.0 Beta 2. The studied area is approximately 14 km2 (5.4 mi2) with a population of approximately 40,000  which is considered a typical midsize community. The building portfolio consists of around 8600 buildings, mostly wooden that areas are typical of US residential communities.
DOI: 10.17603/ds2-mb7z-xw74
title: StEER: Hurricane Otis Preliminary Virtual Reconnaissance Report (PVRR)
title: in StEER - Hurricane Otis

description: This project encompasses the products of StEER's Level 1 and Level 2 responses to this event: Preliminary Virtual Reconnaissance Report (PVRR) with corresponding Media Repository and the Early Access Reconnaissance Report (EARR).
description: Informed by the preliminary evidence compiled in this report, further research is needed to (1) characterize enhanced hurricane risk in a changing climate, where events historically atypical for this region may become commonplace, as will rapid intensifications such as those observed in Otis. This event will further support (2) ongoing study of extreme wind flow within urban canopies with important lessons to be learned for other (and even denser) urban coastal areas. This event also serves as a notable case study to (3) examine extreme wind performance of mid- and high-rise buildings assumed to be governed by seismic loads to advance our understanding of multi-hazard design. Meanwhile the extreme wind speeds observed in this event, if verified, can enable (4) validation of fragility and vulnerability models at the upper ranges of hazard intensity rarely observed to improve our overall damage and loss modeling capabilities. Finally, the topography in the region, when coupled with the heavy rains in this hurricane, provide notable cases of (5) flood-soil-structure interaction in hilly terrain.
Based on the satisfaction of a majority of the escalation criteria, StEER’s response to this event is escalated to a conditional Level 2, pending coordination with local officials and local researchers/practitioners to access impacted areas and capture perishable data through terrestrial and aerial imaging campaigns.
DOI: 10.17603/ds2-pdfb-d686
title: 21-22 March 2022 Tornado Outbreak Field Assessment Structural Team Dataset
title: in StEER - 21-22 March 2022 Tornado Outbreak

description: Observing damage and documenting successful performance of buildings and other structures. Classes include residential, commercial, and power infrastructure. Methodologies include detailed damage assessments in Fulcrum, deployment of UAS for high-resolution aerial imagery, and deployment of surface-level panoramic imaging devices. Hazard indicators were also captured.
description: This project encompasses only an Event Briefing, an abbreviated StEER response mechanism that shares StEER’s impressions of the event and implications for natural hazard research and practice. Information provided herein was gathered from various websites, news channels, and National Weather Service. Therefore, this briefing does not include insights from detailed field investigations.
DOI: 10.17603/ds2-1zxm-4980
title: Nonlinear analysis of strongback braced frames with varying BRB configurations
title: in Design of BRBs for and Collapse Performance of Strongback Braced Frames with Varying BRB Configurations

description: An overturning design procedure for BRBs was developed and evaluated. A simplified model with a rigid strongback was used to evaluate a broad set of input configurations. A more detailed model with actual member sizes was used to design and evaluate a subset of the input configurations, in order to evaluate the ability of proposed strongback design methods to support configurations without BRBs at every level. Nonlinear time history analysis and incremental dynamic analysis was used to evaluate structural responses and probability of collapse. Summarized results (e.g., peak story drift from each ground motion) and statistics, as well as complete source code for re-running the analyses and re-creating the plots, are provided.
DOI: 10.17603/ds2-6qc3-na67
title: Hurricane Lili 2002
title: in FCMP Ground Level Hurricane Wind Data (1999 - 2008)

description: The Florida Coastal Monitoring Program (FCMP) is a collaborative experimental effort to measure ground level hurricane surface winds. This publication provides data files of ground level wind speed and direction measured along the east coast of Florida during landfall of Hurricanes: Irene 1999,  Gordon 2000, Lili 2002, Charley 2004, Ivan 2004, Jeanne 2004, Dennis 2005, Katrina 2005, Rita 2005, Wilma 2005, Gustav 2008, Hanna 2008 and, Ike 2008. Urbanists, social scientists, structural engineers, and meteorologists, among others, can use these real wind speed measurements and directions in myriad disaster research and planning projects.
description: Portable weather stations were deployed along the coast and/or inland to collect wind observations. This publication provides data files of ground level wind speed and direction measured along the coast during landfall of Hurricane Lili 2002.
DOI: 10.17603/ds2-fzg7-1719
title: Cylinder flow with graph neural network-based simulator

description: This dataset corresponds to a tutorial to learn how to use MeshNet, a model for simulating fluid flows. The MeshNet model is publicly available as open source in Github "Graph Network Simulator (GNS) and MeshNet" (See Referenced Data and Software). GNS is a generalizable, efficient, and accurate machine learning (ML)-based surrogate simulator that uses Graph Neural Networks (GNNs). GNS is a viable surrogate for numerical methods such as Material Point Method, Smooth Particle Hydrodynamics and Computational Fluid dynamics and can be extended to simulate natural hazards. GNS  can handle complex boundary conditions and multi-material interactions. GNS exploits distributed data parallelism to achieve fast multi-GPU training. The dataset in this publication includes training/testing/validating partitions to make GNS learn and simulate fluid flow through a cylinder obstacle. It was created using Computational Fluid Dynamics originally from DeepMind. A link to the dataset is available in Related Data and Software and a contextual paper about the MeshNet is available in Related Works.The data was transformed to `.npz` format for compatibility with the Pytroch-based multi-GPU parallel version of GNS code. Detailed instructions on how to use this data are published along with this version of the dataset and also located as a `README.md` file in the GitHub repository. The documentation lives with the model because instructions may change as the model is versioned in the GitHub repository. The main function of this dataset is for purposes of training new users. Once users know how to run the model they can use other kinds of datasets to train and simulate different natural hazards.
DOI: 10.17603/ds2-6z8d-4k80
title: Investigating Access and Barriers to Use of the San Diego Emergency App for ShakeAlert Through a Multi-Methods Approach

description: This project seeks to develop mutually beneficial relationships with limited-English proficiency (LEP) individuals and communities around the ShakeAlert earthquake early warning (EEW) system. LEP households have no member aged 14+ that speaks only English or speaks English ‘very well’. We are working with the San Diego County (SDC) Office of Emergency Services (OES) and their Partner Relay Communication Network around their cell phone app SD Emergency that delivers ShakeAlert-powered alerts. The goal is to improve app adoption rates and ShakeAlert EEW awareness with trusted, community-based organizations that serve LEP individuals. SD Emergency offers multi-hazard alerting (e.g., boil water notices, weather notifications), providing an opportunity to investigate influences on the likelihood of receiving an EEW alert, considering single modality apps have higher uninstall rates. Through broadly distributed surveys, we seek to understand app usage, potential barriers, understanding of EEW messaging, and anticipated responses to EEW that will improve public alerting through ShakeAlert.
DOI: 10.17603/ds2-91jj-fh94
title: Testbed Experts Survey Report
title: in Expert Survey on Community Resilience Testbed Use and Development

description: Virtual Community Testbeds enable researchers to assess multidisciplinary integrated community resilience models and help decision-makers to make better community hazard mitigation plans. To understand what a testbed actually is in practice and to obtain consensus on the definition of a testbed, a virtual survey is administered to testbed experts. The audience of the project span researchers from diverse disciplines in engineering, social and physical sciences
description: The report describes the responses received from the testbed experts. It also provides details on the composition of the respondents and acknowledges the logistic supports the survey received.
DOI: 10.17603/ds2ct15
title: Hurricane Maria (2017) Simulation. In In Hurricane Maria ADCIRC Surge Guidance System Storm Surge Forecasts.
title: in Hurricane Maria ADCIRC Surge Guidance System Storm Surge Forecasts

description: This simulation was conducted on the Lonestar machine at TACC using the ADCIRC Surge Guidance System. This system runs automatically in the event of an impending hurricane threatening the U.S. Coast. The project contains the wind input file and the maximum water levels computed by ADCIRC for several hurricane Maria advisories.  The fort.22 file represents the wind characteristics for the hurricane.  The maxele.63.nc file represents the maximum water levels computed by ADCIRC (in netCDF format).
description: Hurricane Maria struck Puerto Rico and threatened the U.S. coast in 2017.  In this project, we show results from storm surge forecasts for Hurricane Maria based on the ADCIRC Surge Guidance System framework.  These forecasts take data from the National Hurricane Center wind advisories, and generate storm surge predictions every 6 hours.  In this project, we show the wind inputs used by the model and the computed maximum water levels for several of the advisories.  For more information on the ADCIRC Surge Guidance System and its products, visit 
http://adcirc.org/products/adcirc-surge-guidance-system-forecasts/ 
or go to the Coastal Emergency Risk Assessment web site at www.cera.cct.lsu.
DOI: 10.17603/ds2-5mrf-1z94
title: Field Trial of Microbially Induced Desaturation in Low Plasticity Silt
title: in RAPID Liquefaction Mitigation of Silts Using MID Ground Treatment Method and Field Testing with NHERI@UTexas Large Mobile Shakers

description: Field trials of microbially induced desaturation (MID) were conducted at two sites in Portland, Oregon. Monitoring for the two field trials was performed to evaluate the MID treatment performance and the associated subsurface desaturation. Monitoring data included seismic wave velocities measured with crosshole and downhole techniques, embedded in situ sensors, water chemistry measurements, and recovery and testing of samples for changes in soil properties. Results indicate liquefiable soil at both sites was successfully desaturated and that the desaturation persisted for at least two years post-treatment.
description: RAPID Liquefaction Mitigation of Silts Using MID Ground Treatment Method and Field Testing with NHERI@UTexas Large Mobile Shakers
DOI: 10.17603/ds2-etje-s965
title: Undergraduate Research Experience  (REU) 2019: Advancing the Knowledge on the Performance of Steel Collectors in Steel Building Structures

description: Participated in a team that utilized Lehigh University's Advanced Technology for Large Structural Systems lab to do a experimental project to discover the behavior of steel collectors. The instrumentation, loading protocol, and methodology are recorded in the paper.
DOI: 10.17603/ds2-f9gw-0n74
title: Lightly Cemented Model - GLH01s
title: in Liquefaction resistance of MICP treated sands

description: A lightly cemented model was saturated with a de-aired de-ionized water. The model was subjected to a series of shaking events at 80-g. Shear wave velocity and cone penetration measurements were obtained at select times.
description: A set of 1-m radius centrifuge tests on saturated loose Ottawa sand models treated to various cementation levels and subjected to multiple shaking events.  Changes in cone penetration resistance and shear wave velocity are monitored throughout each test.
DOI: 10.17603/ds2-vcth-er91
title: Eastern Iburi Earthquake Reconnaissance - 2018
title: in GEER - M6.6 Hokkaido, Japan

description: UAS data were collected at the Cow Slide and Water Treatment Plant Sites; LiDAR data were collected for the Dam, Port, Highway 59, Satozuka, and Yoshino sites. LiDAR was collected by means of Terrestrial Laser Scanning (TLS) and UAS data was created through the use of SfM (Structure from Motion) from drones.
description: Reconnaissance data of landslides and damages caused by liquefaction triggered by the 2018 M6.6 Hokkaido Eastern Iburi Earthquake. These data were collected as part of the GEER reconnaissance mission: 2018 M6.6 Hokkaido Eastern Iburi Earthquake to document the impacts and distribution of landslides and liquefaction following the earthquake. Terrestrial LiDAR and UAV data were collected from Sept. 27 – Oct. 2, approximately three weeks after the earthquake on Sept. 6th. HazMapper link provides overview of the various LiDAR and UAV data sets, while this repository includes all raw and processed data (in some cases raw data has greater resolution/quality). The intended audience is researchers and officials seeking to understand the impacts of these events, and aid in quantifying the magnitude and form of these landslide and liquefaction features. Further details on these datasets are available in the original GEER report: DOI:10.18118/G6CM1K
DOI: 10.17603/ds2109x
title: KMD01 Centrifuge testing of saturated sand (DRo=43%)
title: in Effect of strain history on cone penetration resistance and cyclic strength of saturated sand

description: This series of tests demonstrate the use of dynamic centrifuge model testing to develop CPT based correlations for the cyclic strength of soil. Level profiles of saturated Ottawa sand were subjected to multiple shaking events until the models were no longer liquefiable.  In-flight cone penetration tests track the progressive change in relative density over multiple shaking events. Dense arrays of accelerometers and pore pressure transducers provide the basis for computing cyclic stress ratios, shear strains, and volumetric strains through inverse analyses. These tests with clean sand facilitate comparison of the results with liquefaction triggering correlations developed by other means.
description: Changes in CPT and cyclic strength of saturated sand across multiple shaking events
DOI: 10.17603/e9wq-gz57
title: GLOBAL ACADEMIC HAZARDS AND DISASTER RESEARCH CENTERS DATA

description: The Natural Hazards Center at the University of Colorado Boulder has compiled a novel data set featuring more than 350 academic hazards and disaster research centers around the world. This project was launched in an effort to allow for more systematic and rapid identification of hazards and disaster research centers and to increase connections, communication, collaboration, and access to emerging research both within and across nations. This data can be used to identify centers by geographic location in the event of a disaster, and, eventually, this data set will be updated to include more information regarding disciplinary and topical expertise within each center. At present, the data set includes a comprehensive list of centers including center name, institutional affiliation, website, city, administrative area (state, province, region), country, latitude, longitude, UN primary region, UN sub region, and center logo. To see the global centers map and to view the complete listing of Centers, please visit: https://hazards.colorado.edu/resources/research-centers. This data set will be updated annually as new centers and information resources continue to be added to the map and associated listings.
DOI: 10.17603/ds2-7nvg-hd61
title: StEER - 26 November, 2019 Albania, Mw 6.4 Earthquake: Event Briefing

description: On November 26, 2019, at approximately 3:54 am local time, a magnitude 6.4 earthquake, with a depth of 20 km, struck 12 km WSW of Mamurras, Albania. This Event Briefing (1) provides details of this earthquake, (2) describes damage to buildings and other infrastructure as well as disruption to the community, in terms of downtime and economic losses, (3) lists key lessons learned, and (4) demonstrates the use of Natural Language Processing (NLP) for rapidly generating brief reconnaissance reports making use of news and social media. Information provided herein was gathered from various websites, news channels, and the USGS. Therefore, this briefing does not include insights from detailed field investigations.
DOI: 10.17603/ds2-fv1f-6v64
title: EERI VERT Albania Earthquake Phase 1 Report

description: The EERI Virtual Earthquake Reconnaissance Team (VERT) is a team of volunteers that activate after major earthquakes to curate reports on the impact to the community. VERT activates in a series of phases after an earthquake to assist in-field teams with data-driven reconnaissance. This report is VERT's Phase 1 report for the M6.4 Albania Earthquake on November 26, 2019. It summarizes the impacts to the region on a variety of different topics. This report is based on publicly available data within 48 hours of the events. The assessment provided in the report is performed by the judgment of the authors with limited access to ground-truthing.