cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17603/ds2-95kg-y369
title: A Framework to Guide Performance-based Assessment of Buildings Following Extreme Events

description: This project includes supplementary information of a manuscript titled "A Framework to Guide Performance-based Assessment of Buildings Following Extreme Events."
DOI: 10.17603/ds2-9w9v-my55
title: Virtual Survey on Community Resilience Testbeds Development and Use
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 mission of this field research was to conduct an expert survey via Qualtrics to understand what it means to be a testbed and to obtain a consensus definition for the term testbed. The survey results are used to write a State of the Art Review paper on virtual community resilience testbeds.
DOI: 10.17603/ds2-bsvv-sx34
title: Natural Hazards Research Summit 2024: Social Science Extreme Events Research (SSEER) Network: Reports on the Status of the Workforce

description: This poster summarizes work from the National Science Foundation-funded Social Science Extreme Events Research (SSEER) network. SSEER was formed, in part, to respond to the need for more specific information about the size, status, and expertise of the social science hazards and disaster research workforce. SSEER serves as the network home for social scientists who study the human, economic, policy, and health dimensions of disasters. As of January 1, 2024, the SSEER network included 1,620 members globally. This poster highlights key membership characteristics including geographic location, research methods used, disciplinary background, and disasters studied. Those who are interested are encouraged to visit our website to access annual SSEER Census reports, SSEER data publications, and the SSEER interactive map (see: https://converge.colorado.edu/research-networks/sseer/). The results of this work have implications for training, mentoring, and workforce development initiatives geared toward ensuring that a diverse next generation of social science researchers is prepared to study the root causes and social consequences of disasters.
DOI: 10.17603/ds2-mn4s-b091
title: NHERI Computational Academy Data Report 2024

description: This report summarizes the 2024 evaluation of the NHERI Computational Academy (NCA) conducted by TACC’s STEM Evaluation Services team. The team examined the implementation, outcomes, and impacts of the NCA using the NHERI Computational Academy survey. The NCA survey gathered information on participants’ background, their satisfaction with the academy, their knowledge gained, whether and how they plan to use what they learned, and their suggestions for improvement. 

 

The NCA survey findings indicated high overall satisfaction among participants. Respondents reported substantial gains in multiple areas, including SimCenter and DesignSafe tools, data analysis, programming, and specific projects or topics. In addition, participants valued the training sessions, assignments, hands-on experiences, and networking opportunities provided by the NCA. Many plan to apply what they learned in the NCA to their own research and established meaningful connections with other researchers. The NCA participants suggested extending the duration of the academy, going into more details on the learning content, mentoring and teaching more efficiently, accommodating various levels of prior knowledge, managing project groups better, offering more hands-on opportunities, and providing more information on the projects early on.
DOI: 10.17603/ds2-p6vg-7s84
title: Natural Hazards Research Summit 2024: An Overview of Indicators for Community Resilience Assessment Methodology

description: Community resilience is a complex, multi-dimensional problem that requires the expertise of various disciplines, such as engineering, social sciences, and earth sciences, to improve the way communities prepare for, resist, respond to, and recover from disruptive events, whether natural or human-caused.
The Community Resilience Program at the National Institute of Standards and Technology (NIST) focuses on research, community planning and guidance, and stakeholder engagement. The Community Resilience Assessment Methodology team helps communities and researchers assess resilience at the community-scale based on community functions, supported by buildings and infrastructure systems, and the recovery of those functions following a disruptive hazard event.
This poster offers an overview of the foundational products, which provides tools, metrics, and guidance for the measurement of baseline resilience and changes in resilience over time.
DOI: 10.17603/ds2-q8eb-p058
title: Natural Hazards Research Summit 2022: NHERI Boundary Layer Wind Tunnel Experimental Facility

description: This poster describes the experimental resources and user services provided by the NHERI Boundary Layer Wind Tunnel (BLWT) Experimental Facility (EF) at the University of Florida. The EF provides users access to state-of-the-art wind engineering experimental resources to accelerate research discovery in wind hazard characterization and mitigation. The poster provides potential users information to start planning their own research utilizing the EF and provides a road map for taking an idea from inception to close-out with the support of the EF PIs and staff.
DOI: 10.17603/ds2-sqrw-az03
title: Modeling Dynamic Systems Through 3D Printing
title: in 3D-Printing Dynamics Design (3D3) Competition – Fall 2023

description: The report involves the application and testing of dynamics concepts through the use of 3D-printed components. It includes various challenges promoting innovation and critical thinking. Challenge 1 focused on exploring angular motion through the design of a 3D-printed wheel. In Challenge 2, a shake table was developed by creating a reciprocating mechanism that converted rotational-to-linear motion. The kinematic relations of the 3D model were derived from the geometry of the mechanism to meet a targeted acceleration. Challenge 3 applied structural dynamics concepts by designing columns of a structure to meet a natural frequency. Challenge 4 built upon previous challenges to test a structure and shake table under forced vibrations. The results from the experiment were used to analyze the dynamic response of a structural system. The challenges integrated 3D design and mathematical modeling to understand the importance of dynamic behaviors in structural engineering.
description: The 3D-printing Dynamics Design (3D3) Competition intends to train School of Civil Engineering & Environmental Science (CEES) undergraduates at the University of Oklahoma in fundamental concepts related to vibrations, structural dynamics, and earthquake engineering through a semester-long, hands-on competition run in parallel with Introduction to Dynamics for Architectural and Civil Engineers (CEES 3263). Competition participants, or 3D3 Scholars, design, build, and test a bench-scale shake table using 3D-printed components. The designs of these shake tables are published here, along with all the STL files needed for teachers or students elsewhere to fabricate the tables. Also, the data collected during the challenges is published.
DOI: 10.17603/ds2-xpyf-sv77
title: A land use policy analysis method for regional natural hazard risk mitigation

description: This project estimates damages and economic losses from hurricane impact under different land use policy scenarios in eastern North Carolina over a 30-year projection period. This analysis also compares expected losses with expected property tax revenue under the different scenarios.
DOI: 10.17603/ds2-0nr1-8571
title: CT1780 | Experiment-Based Column Performance Database - RP1

description: The created column database, collecting column tests from the United States and New Zealand, includes column dimensions, materials, design codes, reinforcement details, experimental column boundary conditions, experimental lateral strengths and displacements, and computed shear capacities from concrete and transverse reinforcement, in addition to damage state descriptions and corresponding limit state values. The documents describing the experimental tests are linked in the column database so that users can directly download the documents through the column database. Steel yield strengths were recorded for longitudinal and transverse reinforcements, respectively. The transverse reinforcement spacings were categorized as inside and outside plastic hinge regions. The spacing inside plastic hinge regions was used to distinguish column design eras, whereas the spacing outside plastic hinge regions was used to determine the minimum column shear capacity. Both transverse reinforcement ratio and transverse volumetric ratio are provided in the column database. The values of the transverse reinforcement ratio and transverse volumetric ratio are different for rectangular columns. The 199 columns were classified into “Era-3 Flexural Columns” (48 columns), “Era-2 Flexural Columns” (71 columns), “Era-1 Flexural Columns” (16 columns), “Era-1 Lap Spliced Flexural Columns” (7 columns), “Era-3 and Era-2 Shear Columns” (32 columns), “Era-1 Shear Columns” (22 columns), and “Era-1 Lap Spliced Shear Columns” (3 columns). Seven column damage state thresholds (CDSTs) are used in the column database to depict damage states and corresponding displacement ductility values. 

The development of such a new column performance database and column capacity limit state (CCLS) models for collecting comprehensive and harmonious CCLSs is necessary due to incomplete and missing data in some of columns in the PEER structural performance database (Berry et al., 2004). There are 416 columns in the PEER database, while 199 columns were recently collected in a resource package (RP1) of this project. The overlap percentages of flexural columns, mixed flexure-shear columns, shear columns, and lap-spliced columns are respectively 63%, 58%, 57%, and 31% of the corresponding columns in RP1. Besides, the classification algorithm for column failure modes adopted in the PEER database is not accurate enough for all columns. Thus, RP1 re-assigns a failure mode to each column.
DOI: 10.17603/ds2-0xzg-2s40
title: Graph Network Simulator
title: in Unveiling Debris Flow Dynamics: Physics-Informed Machine Learning via MPM Simulation

description: Tsunamis, landslides, and other storm-surges can mobilize debris, compounding the hazards faced by built environments. Predicting the dynamics of debris flow in these events is challenging due to the varying materials and their properties. This study presents a novel approach to address this challenge using a combination of machine learning (ML) and advanced numerical simulation. For the creation of lightweight surrogate models, leveraging the highly flexible Graph Network Simulator (GNS), we introduce a wave flume simulation software for debris flows using the Material Point Method (MPM), implemented within the Taichi framework. By utilizing high-performance computing and deep learning networks, this approach enables the efficient representation of complex physics and facilitates uncertainty quantification in debris hazard events. This project allows for easy generation of debris flow data from various materials. The project contents are intended to be used by other researchers in the field.
description: Graph Network-based Simulator (GNS) is a framework for developing generalizable, efficient, and accurate machine learning (ML)-based surrogate models for particulate and fluid systems using Graph Neural Networks (GNNs). GNNs are the state-of-the-art geometric deep learning (GDL) that operates on graphs to represent rich relational information (Scarselli et al., 2008), which maps an input graph to an output graph with the same structure but potentially different node, edge, and global feature attributes. The graph network in GNS spans the physical domain
with nodes representing an individual or a collection of particles, and the edges connecting the vertices representing the local interaction between particles or clusters of particles. The GNS computes the system dynamics via learned message passing. Figure 1 shows an overview of how GNS learns to simulate n-body dynamics. The GNS has three components: (a) Encoder, which embeds particle information to a latent graph, the edges represent learned functions; (b) Processor, which allows data propagation and computes the nodal interactions across steps;
and (c) Decoder, which extracts the relevant dynamics (e.g., particle acceleration) from the graph. The GNS learns the dynamics, such as momentum and energy exchange, through a form of messages passing (Gilmer et al., 2017), where latent information propagates between nodes via the graph edges. The GNS edge messages are a learned
linear combination of the interaction forces. The edge messages are aggregated at every node exploiting the principle of superposition. The node then encodes the connected edge features and its local features using a neural network.
DOI: 10.17603/ds2-1k0a-dt17
title: A Novel Experimental Database on the Cyclic Response of Mine Tailings

description: This study presents an experimental database focused on the cyclic response of mine tailings compiled from various sources. The database is organized considering three classes. Class A contains cyclic simple shear (CSS), triaxial (Tx), and cone penetration testing (CPTu) information, Class B has CSS and Tx or CPTu information, and Class C has only CSS information. Most materials belong to Class A. Of note, Class C is comparable with most databases for natural soils; hence, highlighting the uniqueness of our database. This data can give valuable insight into the field and lab scale response of mine tailings to cyclic loading.
DOI: 10.17603/ds2-2kp1-cc91
title: StEER: 2023 Ecuador Earthquake Preliminary Virtual Reconnaissance Report (PVRR)
title: in StEER - 18 March 2023, Ecuador, Mw 6.8 Earthquake

description: On March 18, 2023, a Magnitude 6.8 earthquake occurred in Ecuador, which caused substantial damage to the cantons and cities within the three provinces of El Oro, Guayas, and Azuay nearest to the epicenter. At least 45 aftershocks were reported one day after the event, with the largest aftershock reaching a magnitude of 4.9. The largest peak ground acceleration was 0.32g for the north-south component recorded at Machala, approximately 53 km from the epicenter.
Fortunately, the number of lives lost and injuries from this earthquake were remarkably low, resulting in only 14 deaths and 494 injuries in comparison to the 2016 event. Still, the Balao earthquake caused damage to over 900 structures. In general, engineered structures (commercial, and government buildings and multi-family residential structures) performed well, exhibiting only non-structural damage. The earthquake drew attention to the vulnerability of historic buildings, and non-engineered (mainly residential) structures built using flexible reinforced concrete frames in combination with stiff infill masonry.
The earthquake highlights the need for more research into retrofit solutions that address the incompatibility of stiff brick/concrete infill masonry and reinforced concrete frames. This is particularly important for non-engineered buildings where inadvertent design choices yield extremely flexible reinforced concrete frames. New construction should encourage the use of alternative structural systems using lighter cladding materials that retain some aesthetic characteristics that make these stiff infills appealing (moderate cost, simple construction methods, and acoustic isolation), but are more compatible with the displacement tolerances of structural framing. This project encompasses the products of StEER's response to this event: Preliminary Virtual Reconnaissance Report (PVRR) and Media Repository.
description: The PVRR is intended to:
1. provide an overview of the Mw 6.8 Balao Earthquake, particularly relating to the earthquake impact on the built environment,
2. overview the regulatory environment and construction practices in the affected area, 
3. synthesize preliminary reports of damage to buildings and other infrastructure, and
4. provide recommendations for continued study of this event by StEER and the wider engineering reconnaissance community.
The PVRR includes both the official report as well as a supplementary media repository containing additional imagery gathered by the VAST as well as a disruption/outage/restoration chronology. As the product of entirely virtual reconnaissance, the PVRR is not based upon detailed field investigations by StEER.”
DOI: 10.17603/ds2-9nqb-b991
title: Comparison of numerical integration methods using a vRTHS of a 3 story steel frame
title: in Recent advances in computational methodologies for real-time hybrid simulation of engineering structures

description: vRTHS where the physical substructure is an actuator with a one-bay one-story steel frame and the numerical substructure is a three-story steel frame. The CATS controller is implemented to synchronize both substructure and different integration methods can be compared using different earthquakes and partitioned cases.
description: This project is part of the review paper about recent advances in computational methodologies for real-time hybrid simulation of engineering structures. The project contains the data, models and codes used for the comparison of numerical integration methods for RTHS using a benchmark problem.
DOI: 10.17603/ds2-at09-7k25
title: Natural Hazards Research Summit 2024: Development of an Equity-Based Infrastructure Metric for Improved Community Resilience to Hazards

description: A novel infrastructure equity metric to assess the service performance inequity is derived that can be integrated alongside traditional least cost and performance metrics in infrastructure decision-making. The equity metric is based on Theil’s T and measures the service inequity between two groups, such as a vulnerable and non-vulnerable group of concern. The metric is first implemented in a hypothetical compact electric grid relative to a hurricane hazard to understand the equity metric’s performance. The metric is further applied in Galveston’s electric distribution network for a hurricane hazard to assess the current inequity state and inequity reduction achieved through retrofit. This metric could be used by decision-makers to incorporate equity in their infrastructure decisions.
DOI: 10.17603/ds2-dcq1-y294
title: Undergraduate Research Experience (REU), NHERI 2019: Seismic Performance of a Steel Structure Using SAP 2000

description: This summer's research project was conducted under graduate student Chao-Hsien Li and Professor Chia-Mia Uang specifically studying seismic performance of collectors in steel buildings. The purpose of this paper is to compare the experimental results from the static pull test and white noise test to the theoretical results from the SAP 2000 model. The static pull test and white noise test were conducted in three stages: steel frame only, steel frame plus composite deck, and steel frame plus composite deck and weights. This paper will focus on the testing of the bare steel frame and the frame plus the composite deck.
DOI: 10.17603/ds2-eahz-9466
title: Cyclic Direct Simple Shear Tests - Ottawa F65
title: in Direct Simple Shear Testing on Ottawa F50 and F65 Sand

description: Pretriggering, triggering, and post-triggering response of Ottawa F65 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-qy0d-wv59
title: Hurricane Florence Twitter Data

description: Collected all tweets from a 12-day period from when Florence first formed until remnants left the U.S. Tweets were collected using Twitter API searching for keywords of wind and water threats that co-occurred in the same tweet. Search terms included the following: ((tornado OR #tornado OR \"funnel cloud\” OR funnelcloud) (\"flash flood\” OR flood OR flashflood OR \"storm surge\" OR stormsurge)). Tweets were classified into three categories: public user (e.g. seeking information and sharing personal experience), authoritative user (e.g. sharing information but not personal information), or other (e.g. private or deleted accounts and bots). Tweets were classified into three categories: public user, authoritative user, or other. After classification, Twitter was re queried via the API to collect contextual tweet streams (entire user history) for the 12-day period for public and authoritative users. As January 2021, the dataset contains 60,007 tweets from 159 authoritative users and 43,783 tweets from 351 public users.
DOI: 10.17603/ds28d6n
title: Test Array 1
title: in NHERI@UTexas Nonintrusive Sinkhole 3D-Imaging Workshop

description: 3D Seismic Survey at Lines O to S:
- Test area of 36 x 12 m
- 48 receivers located in 24 x 4 grid
- 65 shots located in 13 x 5 grid
- Thumper shaking active source
- See "Sinkhole Workshp dataset Summary 20171117.pdf" file for more information
description: NHERI@UTexas hosts a one-day (on October 26th and 27th, 2017), nonintrusive, 3D-imaging of sinkholes workshop at a site near Newberry, FL on State Road 26 in Alachua County. The workshop includes a half-day of seminar followed by a half-day field demonstration. This workshop highlighted a potential use of NHERI@UTexas equipment for true 3D non-intrusive imaging of geotechnical systems using full waveform inversion. Specifically, during the workshop, the urban, mobile, hydraulic shaker named Thumper was utilized to generate dynamic vertical loadings at a Karstic Limestone Geophysical Ground Proving (KLGGP) site in Alachua County, Florida. Two sets of data were collected at the KLGGP site between October 23, 2017 and October 25, 2017.  Test setup are designed by Profs. Dennis Hiltunen (University of Florida) and Khiem Tran (Clarkson University) as a piggyback research project supported by the National Science Foundation (CMMI 1637557, titled: “Geotechnical Site Characterization with 3-D Seismic Waveform Tomography”, PI: Khiem Tran).