cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17603/ds2-11y2-bg84
title: Interviews with NWS Forecasters related to severe weather and new artificial intelligence/machine learning (AI/ML) guidance predicting severe hail and storm mode: Pre-interview survey data
title: in Interviews with National Weather Service (NWS) forecasters related to severe weather and new artificial intelligence/machine learning (AI/ML) guidance predicting severe hail and storm mode

description: This workbook contains two spreadsheets: 1) anonymized online pre-interview survey data and 2) the survey response key. The survey data distinguishes whether the respondent received the "AI/ML" or "No AI/ML" version of the survey.
description: This project developed a pre-interview survey, interview protocols, and materials for conducting interviews with expert users to better understand how they assess and make use decisions about new AI/ML guidance. Weather forecasters access and synthesize myriad sources of information when forecasting for high-impact, severe weather events. In recent years, artificial intelligence (AI) techniques have increasingly been used to produce new guidance tools with the goal of aiding weather forecasting, including for severe weather.

For this study, we leveraged these advances to explore how National Weather Service (NWS) forecasters perceive the use of new AI guidance for forecasting severe hail and storm mode. We also specifically examine which guidance features are important for how forecasters assess the trustworthiness of new AI guidance. To this aim, we conducted online, structured interviews with NWS forecasters from across the Eastern, Central, and Southern Regions. The interviews covered the forecasters’ approaches and challenges for forecasting severe weather, perceptions of AI and its use in forecasting, and reactions to one of two experimental (i.e., non-operational) AI severe weather guidance: probability of severe hail or probability of storm mode.

During the interview, the forecasters went through a self-guided review of different sets of information about the development (spin-up information, AI model technique, training of AI model, input information) and performance (verification metrics, interactive output, output comparison to operational guidance) of the presented guidance. The forecasters then assessed how the information influenced their perception of how trustworthy the guidance was and whether or not they would consider using it for forecasting.

This project includes the pre-interview survey, survey data, interview protocols, and accompanying information boards used for the interviews. There is one set of interview materials in which AI/ML are mentioned throughout and another set where AI/ML were only mentioned at the end of the interviews. We did this to better understand how the label “AI/ML” did or did not affect how interviewees responded to interview questions and reviewed the information board. We also leverage think aloud methods with the information board, the instructions for which are included in the interview protocols.
DOI: 10.17603/ds2-4355-wc05
title: A Machine-Learning Based Predictive Model for Liquefaction Ejecta Manifestation in Stratigraphically Variable Sites

description: This project presents a machine learning based probabilistic predictive model for estimating the potential severity of free-field surface ejecta in stratigraphically variable and interbedded deposits as a measure of liquefaction manifestation and damage. Results from the numerical database used to create the model are also provided which includes 19,760 fully-coupled, nonlinear, dynamic, effective stress, finite element analyses of free-field soil columns in 3D subject to 1D vertical propagation of horizontal shear waves.
DOI: 10.17603/ds2-wn5z-w402
title: Emergency Alerts and Language Access: An Annotated Bibliography
title: in Best Practices and Recommendations for Inclusive Emergency Alerts in Colorado

description: Included here are data and research materials that supported the investigation of emergency alert and warning systems in Colorado developed in accordance with Colorado House Bill 23-1237 (https://leg.colorado.gov/bills/hb23-1237). The aim of the project was to identify how to improve emergency alerting for people who speak non-English languages and have auditory or visual disabilities. First, we include two annotated bibliographies with over 60 publications on topics related to alert and warning systems, disability access, and language access published in the last 20 years. Second, we include a dataset of survey questions, along with the 222 responses from emergency response personnel in Colorado involved in alert and warning activities.  Lastly, we also include a data dictionary, partner meeting questionnaire, recruitment materials, and a sample letter of support from a key partner. These data and materials could be used to review relevant publications on this topic and to aid in developing future surveys focused on alert and warning systems. For final report and additional project context, see project webpage: https://hazards.colorado.edu/research-projects/colorado-inclusive-language-and-access-in-emergency-alerts.
description: The literature review focused on populations with limited English proficiency and language access in emergency alert systems. This literature review supports the State of Colorado’s Inclusive Language Bill HB23-1237. Literature included was published in the last 20 years (2003-2023), was in English, and focused on the United States. These references were compiled through searching Web of Science, EBSCOhost, ProQuest, Google Scholar databases, and agency websites.
DOI: 10.17603/ds2-a66f-t783
title: Natural Hazards Research Summit 2022: Uncertainty Quantification for Global Geospatial Liquefaction Models

description: Geospatial natural hazard models are simple empirical models that take advantage of broadly available geospatial proxies that capture location-specific information on geologic, geomorphologic, and hydrological characteristics and have predictive power for natural hazard predictions. Such models are useful for regional hazard assessments in both post-disaster response and pre-disaster planning phases. Due to the intrinsic variability of natural hazards, model simplification, and measurement errors, the accuracy and uncertainty of these geospatial models vary from region to region and event to event. There is a strong research need to quantify the uncertainty of geospatial natural hazard models to guide future data collection and model updating. We present a framework that addresses this problem by quantifying three types of uncertainties in geospatial natural hazard models: parametric uncertainty, model bias, and input uncertainty of geospatial proxies. We employ forward uncertainty propagation to illustrate how different types of uncertainties affect the outputs of geospatial natural hazard models. The proposed uncertainty quantification framework provides a measure of uncertainty on model predictions and can be applied to any logistic regression models and other geospatial modeling problems.
DOI: 10.17603/ds2-bny7-6957
title: Social Science Methods: Tips for Writing Fieldnotes—CONVERGE Extreme Events Research Check Sheets Series

description: This check sheet reviews the different types of fieldnotes that researchers may use while observing at a research site. Tips for writing up fieldnotes—including organization and the importance of specificity, clarity, and precision—are also provided. About the CONVERGE Extreme Events Research Check Sheets Series: The National Science Foundation-supported CONVERGE facility at the Natural Hazards Center at the University of Colorado Boulder has developed a series of short, graphical check sheets that are meant to be used as researchers design their studies, prepare to enter the field, conduct field research, and exit the field. The series offers best practices for extreme events research and includes check sheets that are free to the research community. More information is available at: https://converge.colorado.edu/resources/check-sheets.
DOI: 10.17603/ds2-wj1h-q563
title: UHPC Tension Strip Test (TST)
title: in Database for Material Characterization of Ultra-High-Performance Concrete (UHPC)

description: A set of UHPC material tests was performed at the University of Houston Structural Laboratory using cylinder compression tests, direct tensile tests (DTTs), and four-point bending tests. Two UHPC mixes were used: one by Steelike® and one by Tindall Corporation. All UHPC matrices included a 2.0% fiber content by volume with 0.5-in. long high-strength steel fibers produced by HiPer Fiber LLC. 
This test database can support analytical modeling of UHPC materials, statistical analyses, or other UHPC material characterization studies. Funding for the reported tests was received by the ACI Foundation with support by Steelike® and the PCI Daniel P. Jenny Fellowship with support by Tindall Corporation.

A new tension test setup for UHPC and associated test data are also included in this database. The test setup involves large-scale tension rebar-free strip tests (TSTs) that were performed to investigate size effects in the tensile behavior of UHPC and correlate them to the small-scale direct tension tests (DTT) per AASHTO T397 [1]. The intent of TSTs was twofold: (a) compare the large-scale (gage length of 35 in. [890 mm]) tension behavior of UHPC with the small-scale (gage length of 4 in. [101.6 mm]) DTTs, and (b) modify the fixed support conditions of DTTs to pin support conditions in the TSTs to produce a state of pure tension force.
description: A new tension test setup involving large-scale tension rebar-free strip tests (TSTs) was developed to investigate size effects in the tensile behavior of UHPC and correlate them to the small-scale direct tension tests (DTT) per AASHTO T397. The intent of TSTs was twofold: (a) compare the large-scale (gage length of 35 in. [890 mm]) tension behavior of UHPC with the small-scale (gage length of 4 in. [101.6 mm]) DTTs, and (b) modify the fixed support conditions of DTTs to pin support conditions in the TSTs to produce a state of pure tension force.
DOI: 10.17603/ds2-rzpz-9m67
title: Research Experiences for Undergraduates (REU), NHERI 2023: Considerations for Social Vulnerability Indices in Hazard and Disaster Research

description: This project details the construction of a CONVERGE Extreme Series check sheet on consideration for the application of social vulnerability indices. This project can be used to inform the construction of other check sheets or other guides. This check sheet hoped to address the lack of an accessible, introductory guide to social vulnerability indices in research. This project is targeted towards emerging hazard and disaster researchers.
DOI: 10.17603/ds2-v0fz-qf03
title: Enhancing Research Outcomes by Engaging with Decision Makers—CONVERGE Extreme Events Research Check Sheets Series

description: This check sheet helps researchers develop plans, practical recommendations, and materials to successfully engage with local or state-level decision makers interested in topics related to hazards and disasters. It also includes information on sharing your research and developing collaborations with decision makers. About the CONVERGE Extreme Events Research Check Sheets Series: The National Science Foundation-supported CONVERGE facility at the Natural Hazards Center at the University of Colorado Boulder has developed a series of short, graphical check sheets that are meant to be used as researchers design their studies, prepare to enter the field, conduct field research, and exit the field. The series offers best practices for extreme events research and includes check sheets that are free to the research community. More information is available at: https://converge.colorado.edu/resources/check-sheets.
DOI: 10.17603/ds2bm3c
title: Wall Panel Test 7
title: in NEESR: Seismic Performance of Conventional and Innovative Special Structural Walls

description: Reversed-cyclic pseudo static test of reinforced concrete wall panel representing plastic hinge region of a wall
description: The project explored design and performance limits for structural walls, considering both conventional wall construction practices and innovative construction practices. A principal finding of recent earthquakes (in 2010 and 2011) and laboratory tests from 200 to 2010 is that wall performance is limited by stability and ductility capacity of the flexural compression zone. Given this critical issue, a series of studies on conventional walls and boundary elements constructed with innovative materials (HPFRCC) to establish performance limits for flexural compression failures in reinforced concrete structural walls. Tests were designed to acquire knowledge, improve construction practices, and advance simulation tools. The primary research outcomes include: 

(1)	Completing  tests of eight ordinary boundary element (OBE) prisms at UCLA. The test specimens were detailed according to ACI 318-11 21.9.6.5 with the goal of assessing failure modes and strain capacities as influenced by concrete cover, configuration of transverse reinforcement, and spacing of transverse reinforcement. Based on the tests, a relationship used to assess buckling of longitudinal reinforcement was extended to wall boundaries with typical OBE detailing. 
(2)	Completing tests on 13 special boundary element (SBE) prisms at UC Berkeley. The tests investigated the role of boundary element detailing and wall thickness. The tests indicated that the strain capacity of relatively (< 12 inches) walls with ACI 318 code compliant SBE detailing was less than one percent and that improved detailing or high-performance, fiber-reinforced concrete did not improve the strain capacity significantly. 
(3)	Conducted tests on seven, approximately one-half scale wall panels represented the base of roughly 8 to 10 story walls in a moderately tall building.  The primary test variables were the configuration and quantity of boundary transverse reinforcement, the depth of the neutral axis, and the wall thickness. The test provided essential data to develop a new, displacement-based model for predicting the drift capacity of structural walls with SBE. 
(4)	Developing code change proposals that were approved for ACI 318-14 and additional code change proposals that have been approved for inclusion in ACI 318-19. 
(5)	Creating and documenting a detailed dataset that was uploaded to DesignSafe-ci Data Depot that can be used for future reserarch.
DOI: 10.17603/ds2-k3sf-ra42
title: Tropical Storm Cristobal
title: in Tropical Storm Cristobal

description: The focus of this project was to document marsh and beach erosion and wave attenuation through vegetation from Tropical Storm Cristobal surge and waves. The data can be used by coastal and ecological engineers to develop physics-based models of marsh and beaches as nature-based solutions. The project is unique because field data can be used to validate and calibrate numerical models.
description: Damages to Grand Isle beach and dune and salt marsh in Terrebonne Bay were observed. Both represent nature-based solutions for coastal protection. Multispectral UAV imagery was the primary data collection method.
DOI: 10.17603/ds2-afza-m544
title: U.S. National Science Foundation Natural Hazards Engineering Research Infrastructure (NHERI) Decadal Visioning Study 2026-2035

description: The U.S. National Science Foundation Natural Hazards Engineering Research Infrastructure (NHERI) Decadal Visioning Study 2026-2035 provides the natural hazards research community with strategic guidance for improving the sustainability of civil infrastructure and resilience to natural hazard events beyond 2025. Based on input from the community, this study outlines a range of considerations and opportunities that reflect the current natural hazards environment while effectively anticipating and addressing its future evolution.
DOI: 10.17603/ds2-jcja-3z28
title: Ambient and Forced Vibration Survey
title: in Acceleration Response of a Six-Story Reinforced Concrete Building under Ambient Conditions and Impact Loads

description: Two sets of acceleration data have been recorded in the building. The first set of measurement has been recorded under ambient environmental conditions and it is called as the Ambient Vibration Survey (AVS) on the 13th of January, 2014. The temperature was 11 °C. The second set of measurement has been performed while the building was hit by a bunch of impacts applied by a construction demolishing vehicle. This set is called as the Forced Vibration Survey (FVS). It was performed on the 23rd of January, 2014 at 12 °C.
description: Two sets of acceleration data obtained from a six-story reinforced concrete building under ambient and forced conditions have been presented. The first recording was called as Ambient Vibration Survey (AVS) and performed on the 13th of January, 2014 at 11 °C air temperature while the second recording was named as Forced Vibration Survey (FVS) and performed on the 23rd of January, 2014 at 12 °C. The fourth floor of the building is selected as the measurement floor and the acceleration measurement has been recorded from its four corners. During the measurements, the building was unoccupied. The impact loads were applied on the fourth-story level of the building via a construction demolishing machine. When the building was vibrating the acceleration records were gathered.
DOI: 10.17603/ds2-mzgn-cy51
title: ARkStorm 2.0: Atmospheric Simulations Depicting Extreme Storm Scenarios Capable of Producing a California Megaflood

description: ARkStorm 2.0 is a cross-disciplinary flood emergency management and climate adaptation scenario aimed at quantifying and ultimately mitigating the consequences of "plausible worst case" flood scenarios in California in a warming climate. It builds upon previous disaster contingency and emergency response planning efforts--including the original ARkStorm exercise (ARkStorm 1.0), which was completed in 2010. In ARkStorm 2.0, we update and upgrade the methods used in ARkStorm 1.0 in two key ways: 1) by incorporating, for the first time, the influence of climate change, and 2) by using a systematic, physically-based approach to scenario event selection. To do so, we conduct new simulations by embedding a high-resolution weather model, the Weather Research and Forecasting Model (WRF), within initial and boundary conditions from an existing climate model large ensemble (CESM-LENS).

The data included in this DesignSafe project includes initial condition, forcing, and configuration files for Weather Research and Forecasting Model (WRF) simulations used to develop the hypothetical extreme storm scenarios in ARkStorm 2.0. It also includes WRF output files containing various meteorological variables (including, but not limited to, precipitation, wind, snow water equivalent, and surface runoff) discussed in Huang and Swain 2022 that may be of interest in characterizing natural hazard impacts in the context of the underlying scenario. These data are intended to be widely used and reused in the development of meteorological scenarios, hydrologic simulations, risk assessments, and other activities aimed at quantifying and mitigating natural hazard risk in California stemming from extreme winter storms in a warming climate. Additionally, those interested in conducting follow-on research specifically based on the published ARkStorm 2.0 scenarios may use the data stored here as boundary/initial conditions to conduct new simulations regarding floods, debris flows, landslides, coastal inundation, or other geophysical hazards that might result from extremely heavy precipitation due to atmospheric river storms in California.
DOI: 10.17603/ds2-txhq-t539
title: FLAC model free- field incremental dynamic analysis
title: in Pile Foundations Under Inertia and Liquefaction-Induced Lateral Spreading

description: Nonlinear dynamic analyses were performed to evaluate the effects of ground motion duration on the dynamic response of a pile-supported wharf subjected to liquefaction-induced lateral ground deformations. The numerical model was first calibrated against recorded data from a centrifuge test and then used in an incremental dynamic analysis using a suite of spectrally matched motions with different durations. The nonlinear dynamic analyses were performed for three loading scenarios: combined effects of inertial loads from the wharf deck and kinematic loads from ground deformations, inertial loads only in the absence of liquefaction, and kinematic loads only in the absence of deck mass. The analysis results provided insights on the relative contribution of inertial and kinematic demands on the response of the wharf with respect to motion duration. It was found that the interaction of peak inertial and kinematic loads increases with motion duration. However, the response of the wharf supported by relatively flexible piles having a small diameter (0.6 m) was found to be primarily governed by kinematic demands in long-duration motions. The differences between the effects of motion duration on the response of small-diameter flexible piles and stiff shafts with a large-diameter (2 m) are discussed in the final report.
description: The project specific objectives focused on characterizing factors that affect how inertial and liquefaction-induced lateral ground deformations affect pile performance. Data from five centrifuge tests on pile-supported wharves were used to evaluate the interaction of inertial and kinematic demands on piles. Numerical models were created and validated using the experimental data and were used in nonlinear dynamic analysis to evaluate the effects of strong motion duration and pile inelasticity on the relative contribution of inertial and kinematic loads.
DOI: 10.17603/ds2-vmqv-rj36
title: RAPID EF Team
title: in StEER - Hurricane Michael

description: On October, 10 2018, Hurricane Michael made landfall just south of Panama City, FL with the National Hurricane Center reporting a minimum pressure 919 MB and maximum sustained winds of 150 mph. Regardless of its place in history, Hurricane Michael caused catastrophic damage from high winds over a wide swath that stretched across much of the FL panhandle and inland into southeastern GA and beyond. natural hazards engineering community to swiftly deploy a Field Assessment Structural Team (FAST). This FAST broadly assessed the performance of a representative subset of structural typologies in coastal and inland areas. Its teams conducted assessments between October 13-15, 2018. FAST collected data in Florida from Panama City Beach east and south to Indian Pass and north to Marianna. The communities assessed included: Panama City Beach, Panama City (and surrounding communities), Mexico Beach, Port St. Joe, Apalachicola, a few routes out to barrier islands in the region, and the inland communities of Blountstown and Marianna. As part of an independent yet complementary effort, the RAPID EF continued data collection on November 7-8, 2018 in and around Panama City and Mexico Beach, using a variety of technologies including unmanned aerial vehicles, laser scanners and applied streetview technologies. This self-funded initiative generated an additional dataset that complements the data collected by StEER and is thus curated jointly in this project. This project encompasses the final product of StEER's response to this event: Curated Dataset, linking to previously published products: Preliminary Virtual Reconnaissance Report (PVRR) and Early Access Reconnaissance Report (EARR).
description: Capturing impacts to the built environment using RAPID EF equipment classes including UAS, Laser Scans, 360 Photography and Applied StreetView.