cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17603/ds2-ttdg-s637
title: Computing Spectrum Intensity for Fractionally Damped SDF system (SIdα)
title: in Fractional Order Intensity Measure for High-Confidence Probabilistic Seismic Demand Modeling of Structures

description: Main File for computing Spectrum Intensity for fractionally damped SDF system (SIdα)
description: In performance-based earthquake engineering, probabilistic seismic demand models of structures are essential components that provide probabilistic estimates of earthquake-induced demands as a function of a variable(s) called the ground motion intensity measure (IM). Uncertainties in these models are often dependent on the IM used. In other words, an appropriate IM for response prediction play a pivotal role toward reliable probabilistic seismic demand modeling of structures and subsequently, risk and resilience quantification. To this end, a series of novel fractional order (FO) IMs are proposed to release the constraints of traditional integer order IMs such as peak ground acceleration (PGA), velocity (PGV), and displacement (PGD), etc., to yield improved demand models. The developed FO IMs include peak ground response (PGRα), cumulative absolute response (CARα) and its modified version (CAR5α), spectral acceleration at a period of interest for a fractionally damped single degree of freedom (SDF) system (Sad-Tnα) and for a conventional SDF system with fractional response (Sar-Tnα), spectrum intensity for a fractionally damped SDF system (SIdα), as well as for a conventional SDF system with fractional response (SIrα). Superiorities of the developed FO IMs to the traditional IMs are successfully demonstrated using a coupled soil-bridge models considering liquefaction and laterally spreading effects. This demonstration motivates further investigation of these FO IMs for different types of structures or infrastructure systems where introduction of fractional order intensity measures may similarly help to improve performance predictions. Accordingly, seismic risk estimates founded upon the use of these novel IMs have the potential to enhance the confidence and accuracy in future studies.
DOI: 10.17603/ds2-1w0y-5080
title: JOINT RECONNAISSANCE REPORT (JRR)
title: in StEER-EERI: PETRINJA, CROATIA DECEMBER 29, 2020, Mw 6.4 EARTHQUAKE

description: On December 29, 2020 a magnitude 6.4 earthquake occurred in the Sisak-Moslavina county of Croatia. The earthquake occurred along the Popusko-Petrinja strike slip fault within the Eurasia plate at a depth of 10 km with an epicenter at 45.422°N 16.255°E, three kilometers (km) west-southwest of the city of Petrinja. The maximum intensity of the earthquake was VII (severe) on the Modified Mercalli Intensity (MMI) scale and VIII (heavily damaging) to IX (destructive) on the European Macroseismic Scale (EMS). Due to the earthquake and resulting damage, there were seven fatalities, 26 people were injured, and many hundreds of people were displaced from their homes. The most affected city was Petrinja, but severe damage also occurred in Sisak, Dvor, Glina, Topusko, as well as in Croatia’s capital Zagreb, located approximately 50 km northwest of the epicenter. Damage was also reported in neighboring countries, including Slovenia, located north of Croatia, and Bosnia and Herzegovina, located south of this region of Croatia. This Joint Reconnaissance Report between EERI LFE and StEER will serve as the primary synopsis of this event.
description: The purpose of this Joint Reconnaissance Report between EERI and StEER is to provide timely information on this earthquake, an overview of the hazard characteristics, and a summary of preliminary damage reports to buildings, bridges, roads, and other infrastructure. Moreover, key findings are also summarized with regard to geotechnical failures that include liquefaction, lateral spreading, landslides, sinkholes and damage to the extended levee system along the Kupa, Odra and Sava rivers.  Note that all observations and findings provided in this JRR should be considered preliminary and are based on the limited scope of the Field Investigations led by colleagues in the region.
DOI: 10.17603/ds2-1hm3-2e61
title: University of California, Davis Centrifuge Experiments of the Seismic Interaction of a Liquefiable Soil with a Cantilever Retaining Wall
title: in LEAP-RPI-2020: Seismic interaction of a liquefiable soil with a cantilever retaining wall

description: One centrifuge test (UCD1) was conducted at University of California, Davis (UCD) to evaluate the seismic response of sheet-pile retaining structures in liquefiable soil for the 2020 Liquefaction Experiments and Analysis Project (LEAP-RPI-2020).
description: The Liquefaction Experiments and Analysis Projects (LEAP) is an international collaboration to develop a databank of high-quality centrifuge experimental data and to use this data in calibration and validation of numerical tools of soil liquefaction and associated consequences. LEAP-2020 investigated the performance and seismic interaction of a liquefiable (Ottawa sand) soil with a cantilever retaining wall. A total of twenty-three centrifuge model tests were performed at eight centrifuge facilities, as part of a round robin testing program. The experimental results of these tests are published and shared in this archive as eight separate experiments (one experiment per centrifuge facility). Each “experiment” includes a number of tests and each model test includes one or multiple destructive input excitations. The conducted tests cover a broad range of soil relative densities and input motion conditions. These tests provide valuable information on the trends and sensitivity of the soil-retaining wall response to variations in shaking intensity and soil relative density. The eight centrifuge facilities involved in LEAP-2020 program included Ehime University (Japan), KAIST (Korea), Kyoto University (Japan), National Central University (Taiwan), Rensselaer Polytechnic Institute (USA), University of California Davis (USA), University of Cambridge (UK), and Zhejiang University (China). The “Experimental Data Archive Overview” document provides an outline of the associated organization.
DOI: 10.17603/ds2-pd9h-6k05
title: Ida-BD: pre- and post-disaster high-resolution satellite imagery for building damage assessment from Hurricane Ida

description: Ida-BD is a dataset with 87 pre- and post-disaster satellite imagery pairs with a very high resolution (0.5m/pixel) from Hurricane Ida 2021 in Louisiana, USA. Ida-BD was obtained from the WorldView-2 (WV2) satellite with very high-resolution images taken in Nov. 2020 and Jul. 2021 for pre-disaster and Sep. 2021 for post-disaster. The satellite imagery was collected close to New Orleans city in Louisiana, USA, one of the most impacted areas during Hurricane Ida in late Aug. 2021. Similar to the xBD dataset, we use polygons to represent building segments and provide four damage categories. All annotations were done by the in-house team with quality control.
DOI: 10.17603/ds2-jaa7-3k57
title: Hurricane Gordon 2000
title: in FCMP Ground Level Hurricane Wind Data (1999 - 2008)

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 Gordon 2000.
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.
DOI: 10.17603/ds2-fjqm-sa92
title: Database of Corroded Reinforced Concrete Columns

description: Reinforced concrete (RC) columns are employed in buildings as the primary load-bearing and lateral force-resisting elements. The deterioration of the durability of reinforced concrete (RC) columns would result in insufficient seismic capacity for structures. Despite progress in the literature, the understanding of these columns is still limited due to the complexities brought by the corrosion. Moreover, current building codes are mainly developed for intact RC columns, which exhibit significant scatters in predicting the seismic performance of corroded RC columns. To facilitate future investigations, a database containing comprehensive information about 221 corroded RC columns is presented in this project. Researchers are encouraged to explore the use of this database through data-driven approaches and continuously upgrade it.
DOI: 10.17603/ds2-q22d-bk96
title: GEER Field Reconnaissance
title: in GEER Reconnaissance of 2018 Palu-Donggala Earthquake and Flowslides

description: Field reconnaissance was performed with a range of instrumentation including GPS receivers (base-and-rover configuration of Leica GS18 survey-grade GNSS RTK GPS systems; and a Garmin GPSMAP 64 handheld GPS unit), and unmanned aerial vehicles (DJI Phantom 4 Pro V2, DJI Mavic 2 Pro, and DJI Inspire 2 platform with a Zenmuse X4S camera). Displacement mapping was performed using satellite imagery provided by DigitalGlobe's Open Data Program.
description: The Mw7.5 Palu-Donggala earthquake occurred on 28 September 2018 and caused significant damage in Palu City and the surrounding Central Sulawesi region of Indonesia. The earthquake initiated a series of catastrophic landslides (classified as flowslides), collapsed buildings, and generated tsunami waves that impacted the coast of Palu Bay. The earthquake claimed over 4,000 lives, making it the deadliest natural disaster of 2018. We performed a post-earthquake field reconnaissance and collected perishable data at the sites of five significant flowslides (named for the communities where they occurred: Balaroa, Petobo, Lolu Village, Jono Oge, and Sibalaya), as well as at other damage locations in the mesoseismal region. Our field team consisted of five U.S.-based members, who were sponsored by the U.S. National Science Foundation-supported Geotechnical Extreme Events Reconnaissance (GEER) organization, in collaboration with geologists, geotechnical engineers, and other researchers from Indonesia's Center for Earthquake Studies (PusGen) and the Indonesian Society of Geotechnical Engineers (HATTI) [collectively referred to as the Palu Earthquake "GEER" team]. The GEER team arrived at Palu City on 13 November 2018 and conducted five days of extensive fieldwork using instrumentation from the RAPID Facility, including mobile data collection software, digital imaging systems, high-resolution global position system (GPS) antennas, and unmanned aerial vehicles (UAVs, or "drones"). The resulting dataset includes over 2,000 geotagged photographs, UAV images, GPS coordinates, and other field measurements and observations, as well as associated post-processed geospatial data products (point clouds, digital surface models, orthomosaic images). Additionally, we used remote sensing data (i.e., pre- and post-event satellite imagery) to generate displacement vectors for over 1,200 structures affected by the flowslides.
DOI: 10.17603/ds2-0wjq-0j84
title: Solving inverse problems using differentiable graph neural network simulator

description: Inverse problems in granular flows, such as landslides and debris flows, involve estimating material parameters or boundary conditions based on target runout profile. Traditional high-fidelity simulators for these inverse problems are computationally demanding, restricting the number of simulations possible. Additionally, their non-differentiable nature makes gradient-based optimization methods, known for their efficiency in high-dimensional problems, inapplicable. While machine learning-based surrogate models offer computational efficiency and differentiability, they often struggle to generalize beyond their training data due to their reliance on low-dimensional input-output mappings that fail to capture the complete physics of granular flows. We propose a novel differentiable graph neural network simulator (GNS) by combining reverse mode automatic differentiation of graph neural networks with gradient-based optimization for solving inverse problems. GNS learns the dynamics of granular flow by representing the system as a graph and predicts the evolution of the graph at the next time step, given the current state. The differentiable GNS shows optimization capabilities beyond the training data. We demonstrate the effectiveness of our method for inverse estimation across single and multi-parameter optimization problems, including evaluating material properties and boundary conditions for a target runout distance and designing baffle locations to limit a landslide runout. Our proposed differentiable GNS framework offers an orders of magnitude faster solution to these inverse problems than the conventional finite difference approach to gradient-based optimization.

This DesignSafe repository contains data required to run the inverse analysis for our three demonstration cases (`inverse_friction`, `inverse_velocity`, `inverse_barrier`). Each includes GNS models (along with their metadata), inverse analysis configurations, and ground truth data for optimization targets. To run the inverse analysis with these data, please refer to our differentiable GNS code provided in the GitHub repository "Related Work (https://github.com/geoelements/gns-inverse-examples)".
DOI: 10.17603/ds2-20sx-s182
title: Research Experiences for Undergraduates (REU), NHERI 2022: Non-Invasive Subsurface Modeling with Python Open-Source Packages

description: This project discusses locating sinkholes and carrying out field tests using the T-Rex truck and non-invasive modeling techniques. The data were collected and and analyzed from the tests done in Newbury, Florida. The uploaded data may be used by researchers to carry out their own experiments and is unique in how the data is collected and the completeness of the subsurface picture created. Any researchers  who are interested in understanding soil properties will find this research useful.
DOI: 10.17603/ds2-pwgy-fx23
title: Simulated and Synthetic Data Generation for Interdependent Natural Gas and Electrical Power System Based on Graph Theory and Machine Learning

description: The overall objective of this project is to apply recent advances in machine learning techniques and graph theory to investigate practical data-based approaches for producing simulated and synthetic datasets that faithfully represent interdependence between natural gas networks and power grids from mechanistic and human aspects.
DOI: 10.15468/dl.7ab2xa
title: Occurrence Download

description: A dataset containing 7078 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Sus scrofa Linnaeus, 1758)",
 "Country is one of (Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia (Plurinational State of), Bonaire, Sint Eustatius and Saba, Bouvet Island, Brazil, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Curaçao, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Barthélemy, Saint Kitts and Nevis, Saint Lucia, Saint Martin (French part), Saint Vincent and the Grenadines, Sint Maarten (Dutch part), South Georgia and the South Sandwich Islands, Suriname, Trinidad and Tobago, Turks and Caicos Islands, Uruguay, Venezuela (Bolivarian Republic of), Virgin Islands (British), Virgin Islands (U.S.))"
 ]
}

 The dataset includes 7078 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015646-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17603/ds2-jhfp-3d20
title: Hurricane Jeanne 2004
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 Jeanne 2004.
DOI: 10.17603/ds2-qrev-cj24
title: Undergraduate Research Experience (REU), NHERI 2019: Effects of Modern Residual Stress Patterns on Inelastic Buckling of Hot-rolled Steel Sections

description: Residual stresses, or stresses induced during the manufacturing process, are known to affect the strength of steel members. Due to advancements in technology and accessibility of resources, straightening techniques of steel members have improved to increase efficiency. These straightening techniques have been found to alter typical residual stress patterns. Research was conducted at the University of California San Diego to obtain residual stress patterns within modern steel members with the
objective to suggest that the equations E3-2 and E3-3 provided by AISC Steel Construction Manual may be altered to maximize efficiency.Experimental measurements were taken by adapting a hole-drilling technique to measure strains within multiple I-shape steel members. The strains were used to derive the residual stresses within the members. Residual stress patterns were also applied to 3-dimensional models using the non-linear finite element software ABAQUS to predict the ultimate buckling capacity of members.
DOI: 10.17603/ds2d95g
title: RLH01 Centrifuge Test of Prefabricated Drains
title: in Evaluation of Drainage for Liquefaction Remediation

description: This experiment is a model of a liquefiable lateral spread site that spreads towards a channel.  Three soil improvement treatment zones are included: untreated, treated with non-draining tubes, and treated with draining tubes.  The area with non-draining tubes was included to investigate pinning effects introduced by the tubes.  Instrumentation included pore pressure transducers, LVDTs, and accelerometers.  Earthquake motions and sinusoidal motions were used as the seismic excitation.
description: This project looked at the response of liquefiable sand deposits with and without prefabricated drains installed.  The project involved centrifuge testing, as well as field testing in South Carolina.
DOI: 10.17603/ds2-2fky-tm46
title: Horizon: CPT-based liquefaction risk assessment and decision software

description: Horizon is windows-executable software for analyzing the occurence, consequence, mitigation, and economics of seismically-induced soil liquefaction via CPT sensing and models. Salient features include:

(1) CPT processing: Inverse filtering and interface correction; CPT sensor alignment via statistical cross-correlation. (2) Six triggering models; Four free-field manifestation models; Shallow-foundation fragility and vulnerability models. (3) Seamless integration with USGS probabilistic seismic hazard analysis (PSHA) framework; Compute return periods of free-field manifestation, foundation damage, and economic loss. (4) Cost-benefit analytics for deciding whether/how to mitigate risks; Quantify value of planned or constructed mitigation.
DOI: 10.17603/ds2-jv3x-fp80
title: Sliding Glass Patio Doors with and without Shutter
title: in Lab Tests with Wireless Sensor Network (WSN) system  for the characterization of strong wind loads on non-structural components

description: The goal is to better understand the interaction of hurricane and other strong wind events with non-structural components of residential structures. The objectives are: 1) to develop a new generation of a wireless pressure monitoring system; 2) to deploy the system in large to full-scale tests at the Wall of Wind (WoW); 3) to measure wind pressures on different non-structural components, for different wind speeds and directions;  4) to analyze field and laboratory data to validate and improve current wind loads recommendations and models for pressure distributions on building components.
description: A full scale model of a mock up box with flat roof and a sliding door with 2 panels was tested at different wind speeds (65, 85, 105 mph) and wind directions (0°, 22.5°, 45°).  One panel was glass, on which Florida Tech’s wireless sensor network system (WSNS) patch sensors (from Scanivalve) were fixed with hot glue. The other panel was a plywood panel on which  pressure taps were installed and connected to a Scanivalve (SCV) pressure scanner, by drilling through the panel. The WSNS measured absolute pressure at 10 Hz sampling rate.  The SCV scanner measured differential pressures at 520 Hz. The data from both sensor systems were compared to ASCE 7-16 to study the impact of storms and hurricanes on such a non structural component, with and without aluminum storm panel shutters.
DOI: 10.17603/ds2-xt1n-w752
title: Gravel removal tests
title: in Roof gravel motion initiation

description: Data from this project includes pressure and shear stress measurements from the FIU WOW-EF on a square plan building.
description: destructive testing of gravel roof systems to measure the wind speed required to scour roof gravel from a flat roof with parapet.
DOI: 10.17603/ds2-4s85-mc54
title: Natural Hazards Engineering Research Infrastructure, Five Year Science Plan, Multi-Hazard Research To Make a More Resilient World, Second Edition

description: This is the second edition of the five-year Science Plan for the Natural Hazards Engineering Research Infrastructure (NHERI).
It provides information for constituents, including practitioners, as well as guidance for members of the
research community.This report is an overview of the research needed to support the Grand Challenges described by the report. It covers both the scope and the process of conducting multi-hazard research for improving civil infrastructure.