cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17603/ds2-89h2-de64
title: Focus Group/Survey Instruments
title: in Evaluating National Weather Service Fire Weather Products within a Fire Partner and Public Decision Making Context

description: This study explores the decision-making processes of fire partners in relation to National Weather Service (NWS) fire weather products, such as Fire Weather Watches (FWW) and Red Flag Warnings (RFW). While these products are designed to alert fire management personnel and the public to critical fire weather conditions, there is limited research on how they are actually used in practice. Through 19 focus groups with 85 participants across all six NWS regions, the first phase of this research examines how these partners interpret and use fire weather information from the NWS and other sources to guide operational decisions leading up to wildfires. The second phase entails similar objectives, but through a survey of fire personnel nationwide. The last phase of the research entails the publics perception and understanding of NWS fire weather products. This will be completed via a nationwide survey. Instruments from each phase will be published here as the study progresses.

Audience is for natural hazard social scientists, particularly interested in the fire hazard.
description: This study explores the decision-making processes of fire partners in relation to National Weather Service (NWS) fire weather products, such as Fire Weather Watches (FWW) and Red Flag Warnings (RFW). While these products are designed to alert fire management personnel and the public to critical fire weather conditions, there is limited research on how they are actually used in practice. Through 19 focus groups with 85 participants across all six NWS regions, the first phase of this research examines how these partners interpret and use fire weather information from the NWS and other sources to guide operational decisions leading up to wildfires. The second phase entails similar objectives, but through a survey of fire personnel nationwide. The last phase of the research entails the publics perception and understanding of NWS fire weather products. This will be completed via a nationwide survey. 

Audience is for natural hazard social scientists, particularly interested in the fire hazard.
DOI: 10.21979/n9/v8yrqu
title: Related Data for: Leveraging the Self-Steepening Effect for Optimized Ultraviolet Generation in Gas-Filled Hollow-Core Fibers

description: Ultraviolet (UV) generation in the form of the dispersive wave in gas-filled hollow-core fiber is a powerful technique for developing wavelength-tunable ultrafast UV laser. Here, we present a numerical investigation examining the influence of the self-steepening effect on UV conversion efficiency. By fine-tuning the self-steepening conditions—reducing the pulse width and employing a longer pump wavelength—we can significantly enhance the conversion efficiency of the generated UV light.
DOI: 10.17603/ds2-g7qk-vn39
title: Research Experiences for Undergraduates (REU), NHERI 2023: Experimental Study on Parameters Affecting Computer Vision-Based Structural Displacement and Deformation Monitoring

description: This paper presents an experimental study on the effectiveness of non-contact type vision sensors (i.e., video cameras) to track displacement and deformation in structural testing. This project uses vision-based systems that consist of off-the-shelf commercial video cameras and a video-tracking post-processing program developed by a team at Howard University. This project provides recommendations for the use of vision-based systems in structural testing.
DOI: 10.17603/ds2-577h-e550
title: Establishing a Social Research Infrastructure for Hazards and Disaster Studies – Saskatchewan Canada

description: Establishing a Social Research Infrastructure for Hazards and Disaster Studies in Canada,” funded by the Canada Research Chairs Program (Award # CRC-2020-00128). This project aims to comprehensively asset map the existing hazards and disaster scholars, educational courses, modules, and programs at the post-secondary education organizations in Saskatchewan, Canada. Accordingly, data were collected from the official institution websites of two universities, four federated colleges, six affiliated colleges, one polytechnic, two Indigenous education, and eight regional colleges (https://www.saskatchewan.ca/residents/education-and-learning/universities-colleges-and-schools/post-secondary-institutions#universities), and 31 career colleges (https://www.saskatchewan.ca/residents/education-and-learning/universities-colleges-and-schools/career-colleges#list-of-registers-private-vocational-schools). These data include the information of (1) courses that focus on climate change, hazards, risks, and disasters, and (2) academic programs that are related to the topic of climate change, disasters, and other crises. The original data also indicate faculty members who have expertise in conducting hazard and disaster research. However, faculty members’ data (e.g., names, email addresses, and office telephone numbers) cannot be shared publicly due to privacy and ethical concerns. The users may use the courses and programs information included in this dataset to identify related faculty members. These data illustrate the strengths and weaknesses of hazards-and-disaster-specific post-secondary education resources in Saskatchewan, which might encourage hazards and disaster educators to understand the existing gaps and explore possible solutions. Researchers in Canada and internationally could use these data to navigate their potential research collaborators through related educational programs. Future students could use these data to search for hazards-and-disaster-related programs and courses, as well as contact potential faculty members in related departments. The general public could use the data to further search detailed information associated with the courses and programs they might be interested in as well as identify their community-based scholars through the courses and programs.
DOI: 10.17603/ds2-ggbj-7h62
title: Research Experiences for Undergraduates (REU), NHERI 2023: Engineering with Nature: How Effective are Hybrid Solutions at Reducing Overtopping?

description: My research project was about the potential efficiency of hybrid solutions as coastal protection against wave effects. Mangrove forests were the subject of interest, as we determined their ability to reduce wave overtopping alone, and in a hybrid system with a rock revetment wall. The data collected in this project can be used to measure the wave attenuation and wave overtopping reduction capabilities of the hybrid green and gray infrastructures used. The data can also be used to identify trends in results compared to wave conditions. This project is unique in that it was a large-scale prototype to model the effects of mangrove forests on wave forces and overtopping. It is additionally going to work towards determining scaling factors for mangroves in order to promote small-scale research on green engineering coastal protection methods. The audience intended for this project would be both current and potential engineers looking to find modern, ecological solutions to the threats our coastal communities face. This research can be informative for a wide range of audiences, as it was intended to motivate further research and is therefore preliminary and explained in an introductory manner.
DOI: 10.17603/ds2c687
title: Five story building with tunned mass damper
title: in NHERI UCSD Hybrid Simulation Commissioning

description: The use of large shake tables can provide extended capabilities to conduct large- and full-scale tests examining the seismic behavior of structural systems that cannot be readily obtained from reduced scale testing, or under pseudo-dynamic conditions. When considering large or complex structural systems, however, additional challenges arise such as high costs of full scale specimens or capacity limitations of currently available shake table. Some of these limitations can be overcome by real-time hybrid shake-table substructure test method that requires only key parts to  be evaluated experimentally on the shake table while the remainder of the structure is modeled numerically. As a demonstration of the applicability of this method using a large shake tables, a series of hybrid shake table tests were conducted on the UCSD Large High Performance Outdoor Shake Table (LHPOST) with capabilities to test full scale structural models. A physical specimen was built on the LHPOST, and coupled with a numerical model using hybrid simulation techniques. Comparison of different methods to interface the numerical model with the control systems were evaluated. The physical specimen consisted on a rigid mass resting on four triple friction pendulum bearings that represented the upper story of a shear building model having the effect of  a tune mass damper. Numerical models of shear buildings with different periods and multiple degree of freedom were considered to evaluate the performance of the table and stability and accuracy of the simulation results. The teste results demonstrate the effectiveness of tune mass dampers in reducing structural response and the benefit of using a hybrid shake table test method towards expanded system level dynamic testing. The performance of the shake table is evaluated and methods to compensate delay and other sources of error are discussed.
description: Shake table tests of 5DOF building model with experimental tunned mass damper using UC San Diego shake table (LHPOST). The 5-DOF model was ran using  OpenSees/OpenFresco for the numerical substructure with Simulink for compensation.
DOI: 10.17603/ds2-a1nj-z717
title: Phoenix Cool Pavement Surface Reflectivity
title: in City of Phoenix Cool Pavement Evaluation (COPE)

description: Many cities around the world, including the City of Phoenix, are experiencing elevated temperatures due to the built environment that are exacerbated by climate change. Paved surfaces with impervious materials, such as asphalt concrete (roads, sidewalks, parking lots, etc.), absorb and store heat during the day and release this heat overnight creating higher temperatures than surrounding rural areas. This phenomenon is known as the Urban Heat Island (UHI) effect. 

With paved surfaces comprising about 40% of the urban land area in Phoenix, they are often considered one of the primary causes of the UHI. One of many strategies to mitigate increased temperatures and reduce heat storage in pavements is the use of coatings that reflect (rather than absorb) solar radiation to reduce the heat absorbed by the pavement, thus reducing surface temperatures. Lowering surface temperatures and the heat retained in the built urban environment may help reduce elevated day and nighttime air temperatures. Such reflective coatings are easy to apply to existing paved surfaces and, in most cases, use light-colored pigments and materials to increase reflectivity compared to traditional asphalt concrete roads. 

The City of Phoenix recently initiated the Cool Pavement Pilot Program in which the City applied the product CoolSeal by GuardTop® to 36 miles of residential neighborhood roads and one public parking lot. This effort resulted in the most miles of road surface coverage with a reflective coating of any municipality globally. It is designed to achieve lower pavement surface temperatures through its lighter color and reflectivity. One neighborhood in each of the eight council districts of Phoenix was chosen for application of CoolSeal in consultation and with the support of the City Council Offices.

Data from the Phoenix Cool Pavement Pilot Program are shared through the DesignSafe Data Depot to be accessed by researchers, municipal officials, and other stakeholders seeking to understand the impacts of this particular heat mitigation strategy and/or who may be considering a similar implementation in their jurisdiction.
description: This mission includes datasets of surface reflectivity fieldwork days as part of the City of Phoenix Cool Pavement Evaluation project in 2020-2021 to evaluate the changes of surface reflectivity of a reflective pavement coating that was applied to the streets of eight residential neighborhoods over time. A spectroradiometer, measuring surface reflectivity from 300-2500 nm, was used to measure the surface reflectivity monthly at all 9 locations (8 reflective pavement and 1 asphalt concrete reference) between November 2020 and May 2021.
DOI: 10.17603/ds2-m2v1-ga09
title: Machine learning based seismic bearing capacity prediction for strip footings positioned on the crest of geosynthetic reinforced soil structure

description: Geosynthetic-reinforced soil structures are often used to support shallow foundations of various infrastructure systems including bridges, railways, and highways. When such infrastructures are located in seismic areas, their performance is linked to the seismic bearing capacity of the foundation. Various approaches can be used to calculate this quantity such as analytical solutions and advanced numerical models. Building upon a robust upper bound limit analysis, we created a database comprising 732 samples. The database was then used to train and test a model based on a random forest machine learning algorithm. The trained random forest model was used to develop a publicly-available web application that can be readily used by researchers and practitioners. The model considers the following input factors: (1) the ratio of the distance of the foundation from the edge and the width of the foundation (D/B), (2) the slope angle (beta), (3) the horizontal seismic intensity coefficient (kh), and (4) the dimensionless geosynthetic factor, which accounts for the tensile strength of the geosynthetic. Leveraging the model developed in this study, we show that the most important features to predict the seismic bearing capacity of strip footings positioned on the crest of geosynthetic-reinforced soil structures are D/B and kh.
DOI: 10.17603/ds2-sa8v-0a73
title: Wave 2b: National 2020 Survey
title: in Longitudinal Study of Small Business Resilience to Natural Hazards and COVID-19

description: Between 2019 and 2021, four surveys were deployed to study small business natural hazard preparedness and resilience. Wave 1 focused on Charleston, South Carolina. Wave 2a focused on all coastal North Carolina and South Carolina counties. Wave 2b was a national survey with an abbreviated version of Wave 2a. Wave 3 focused again on Charleston, South Carolina.

This longitudinal study informs our understanding of hazard-experienced small business preparation and response before, during, and after the first year of the COVID-19 pandemic.
description: National online survey in partnership with Alignable (www.alignable.com) studying natural hazards experiences and COVID-19.
DOI: 10.17603/ds2-9hef-9k64
title: Coupon Tests
title: in Computational Simulation of Ductile Fracture in Structural Steel Systems

description: This project enhanced our understanding of the process by which steel structures incur fracture when subjected to strong earthquake effects. The fracture in this case is termed "ductile", because it is driven by the development of inelastic (plastic) deformations. The resistance to fracture initiation and propagation also depends on the stress conditions that a particular region of a structure may experience. Additionally, it may depend on the metal forming process, by which flat steel plates are deformed to give a desired profile shape for a steel member. There is a concern that metal forming may lead to regions in a steel profile, such as the corner regions of a tube profile, where the material resistance to rupture may be different than that in regions away from the corners. 
This research included both physical experimentation and computational simulation. Physical experimentation on small steel coupons up to fracture allowed an understanding of the crack formation and propagation process which may occur at critical regions of steel structural members having a hollow rectangular (tube) cross-section. Metal forming was found to have a fairly minor effect on fracture resistance. Further experimental tests on a structural brace having a tubular cross-section, together with computational simulation, provided insights into the process by which local buckling in the thin walls of the tube entails large localized deformations which ultimately cause the formation and propagation of cracks until full fracture of the brace.
description: This study combined experimental testing and computational simulation to enhance the understanding of structural steel fracture due to low-cycle fatigue. The experiments were conducted in specimens extracted from the flat and corner regions of two rectangular steel hollow sections with different thickness. A total of 60 cylindrical specimens with a circumferential notch were subjected to different combinations of axial and torsional loading. The loading protocols and notch geometry were designed to produce different stress states at the location of fracture initiation. Finite element analyses were conducted to obtain the stress state and inelastic strains at the fracture initiation location. The calibration also allowed the comparative evaluation of the capability of the different laws to capture fracture initiation for different stress states, with a single set of values for the various parameters. These experiments and simulations can be used for further evaluation of existing and new low-cycle-fatigue laws.
DOI: 10.17603/ds2-h0v7-e150
title: Natural Hazards Research Summit 2022: Efficient propagation of aleatoric uncertainties in the hazard description using stochastic emulation

description: One of the most important steps in hazard estimation and consequently in risk assessment efforts is the accurate and detailed description of the hazard itself. This task entails the propagation of all known sources of uncertainty mainly by using a numerical model, and can be distinguished between two main categories: the parametric and aleatoric uncertainties. The former ones can be typically addressed in a systematic way, whether the latter ones pose a bigger challenge, representing commonly higher-dimensional uncertainties or uncertainties without a clear mathematical description, and requiring substantial computational burden to probabilistically characterize their impact on the output of interest. In order to reduce this burden computational statistics tools can be used to promote a fast, yet accurate, risk assessment. A novel framework based on stochastic emulation is developed that allows for the efficient approximation of the full distribution for the output of interest, circumventing challenges associated with the representation and characterization of aleatoric uncertainties. Seismic risk assessment is one example where the developed framework can be applied, addressing the aleatoric uncertainty that stems from ground motion to ground motion variability within the chosen excitation model. The objective here is to provide directly the full engineering demand parameter (EDP) distribution (under the impact of aleatoric uncertainties) within a PBEE vulnerability quantification setting.
DOI: 10.17603/ds2-xmvd-h348
title: building footprint with ffe on Galveston
title: in Galveston Data

description: The project is relevant to the various dataset on Galveston, including the first-floor elevation, building heights and base elevation.
description: The building footprints with First-floor elevation simulated by calculating the distance from Google Street View images.
DOI: 10.17603/ds2-93rk-hz83
title: Data Files for Ground Motion Studies Pertaining to Southern California Basins and Other Geomorphic Provinces

description: This database is part of an on-going effort to compile and process recent earthquake ground motion data for seismic hazard assessment/analysis and model development. The provided database contains computed ground motion intensity measures (pseudo spectral accelerations, peak ground velocities) for processed earthquake time histories from events in Southern California. This includes records from the Next Generation Attenuation West-2 (NGA-West2) Project and data from earthquakes that have occurred since the completion of the NGA-West2 compilation (post-2010) such as, the 2019 Ridgecrest Earthquake Sequence and others. The data provide here was used to assess the site response of basins and other geomorphic provinces in southern California.
DOI: 10.17603/ds2-r46y-g112
title: Natural Hazards Research Summit 2024: Unstructured to Actionable: Extracting Wind Event Impact Data for Enhanced Infrastructure Resilience

description: This project employs zero-shot text classification with pre-trained BART-large models to efficiently extract and analyze critical data on infrastructure and community impacts from wind disaster reconnaissance reports. While primarily focused on wind, the methodology can be applied to various hazards, including earthquakes. It utilizes advanced NLP models including BART-large MNLI and CNN, which eliminates the need for extensive labeled datasets. This approach enables the rapid synthesis of impact information from historical damage reports, essential for informed decision-making and resilience planning. The primary audience includes researchers, disaster managers, and natural hazard engineers, focusing on disaster resilience and response.
For more details and access to the project resources, visit the GitHub repository: Impact-Data-Mining.
DOI: 10.17603/ds2-cejj-cx33
title: ASCE INSPIRE 2023 - DesignSafe Workshop

description: This project directory contains the notebooks and supporting data for the ASCE-INSPIRE 2023 DesignSafe workshop to be held Wednesday November 15, 2023 - https://inspire.asce.org/session/workshop-core-and-designsafe