cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17603/ds2-1jsf-3y68
title: 2023 NHERI GSC Mini-Conference Proceedings

description: The 2023 NHERI GSC Mini-Conference was born out of a desire to share work with fellow graduate students in the natural hazards field. With the climate change crisis, intensifying and increasing disasters, combined with the growing awareness that social and historical disadvantage shapes inequalities in how people experience and are able to adapt to and recover from environmental hazards, there is an incredible demand for innovative and interdisciplinary work that graduate students are on the cutting edge of producing. This virtual conference offered the space to share work, find potential collaborators, and celebrate the successes of our peers. The hard work of these graduate students in natural hazards is recorded here in our first annual NHERI GSC MIni-Conference Proceedings. Here you can explore work from graduate students in civil and environmental engineering, sociology, demography, public health, and other fields in natural hazards discussing multidisciplinary perspectives on resilience, recovery, and risk as well as participants from the first NHERI GSC Interdisciplinary Research Challenge.
DOI: 10.17603/ds2-7ht6-ks16
title: Network resilience trajectories (large scale simulation)
title: in Webinar material: Leveraging HPC Resources at DesignSafe-CI and Interoperability with IN-CORE for Resilience Assessment

description: The models created in the 'small-scale simulation' are leveraged and used to analyze the network recovery trajectories using a larger number of simulations. For completeness, the example corresponds to a transportation network subjected to seismic events.
description: The recent decade has seen a rise in community resilience modeling, including a quest to model infrastructure resilience (its exposure, damage, and restoration) under extreme events. These efforts entail measuring, visualizing, and probing alternatives to support mitigation, recovery, and resilience-enhancing interventions. However, the practice demands developing different input sub-models, considering various layers of uncertainty, and integrating these for the final assessment. 

In this project, we present how the resources of the DesignSafe Cyberinfrastructure (DesignSafe-CI) can support such efforts. We present different tools that can be leveraged from DesignSafe directly or through its interoperability with other platforms, such as the Interdependent Networked Community Resilience Modeling Environment (IN-CORE). We present illustrative examples of how to leverage publicly available data in DesignSafe-CI and models within the IN-CORE platform to create an infrastructure resilience assessment pipeline. These examples are developed and analyzed using JupyterLab in DesignSafe. Furthermore, we present how JupyterLab HPC in DesignSafe-CI enhances the modeling and testing capabilities as the analysis of larger infrastructure systems (e.g., detailed transportation networks) becomes feasible. While the illustrative example uses earthquakes as the hazard type, the leveraged tools, platforms, and shared codes can be adapted to multiple hazards. 

This project is created to share the material presented on December 11 (2024) in the DesignSafe Webinar "Resilience Assessment of Community Infrastructure: Leveraging HPC Resources at DesignSafe-CI and Interoperability with IN-CORE".  You can find the recording of the webinar at the following link: https://youtu.be/Bdb8s4Rc4h4?feature=shared
DOI: 10.17603/ds2-e91y-cv92
title: Reducing the Human Impacts of Flash Floods: Development of Microdata and Causal Model to Inform Mitigation and Preparedness

description: This published project contains the code (in R programming language) and the data used to develop model to understand why unsafe conditions exist during flash flood events and the human impacts (fatalities and injuries) of flash floods. This study has been published here: https://doi.org/10.1007/s11069-023-05845-x. The study (1) identifies climatic, environmental, and situational factors that affect the occurrence of fatalities and injuries in flash food events and provides a predictive model to estimate the likelihood of these occurrences, and (2) develop a model to predict the likelihood of human harm resulting from a flash flood event using these factors in a census tract. Upon testing three variants of the logit model, we found the rare event logistic model (Relogit) to be the best performing one. This model can be used as a simulator tool for informing flash flood mitigation. The file ‘Flash Flood Human Harm.Rmd’ contains the code used to develop the model. The ‘flash_flood_data_all.csv’ file contains the dataset for 6065 flash flood events in the study period 2005-2019. The data were harvested from structured and unstructured data sources on the web like the NOAA Storm Events Database, American Community Survey, National Land Cover Database, TxDOT, Texas Natural Resources Information System, and National Hydrography dataset. Further details are available in the readme file. The remaining two csv files are the train and test files created using ‘flash_flood_data_all.csv’ to train a rare event logistic regression model and test its performance. The assembled data can be used to develop enhanced predictive models for estimating the impacts of future flash flooding at the community scale.
DOI: 10.17603/ds2-kz21-za86
title: Microtremor Data Collection in West LA Region, 2024
title: in Microtremor Measurements Performed in Proximity to Strong Motion Stations Across California

description: The Los Angeles Basin (LAB) is a major sedimentary basin located in southern California, stretching across a broad area that includes much of the city of Los Angeles. This basin is part of the larger Transverse Ranges geologic province and is characterized by a mix of flat lowlands and coastal foothills. The LAB is situated near several active fault systems, including the San Andreas Fault to the north and the Newport-Inglewood Fault to the south, contributing to the region's significant seismic activity. The basin is composed of a range of sedimentary layers that affect seismic waves and ground motion during earthquakes. In the western part of the LAB, 18 microtremor measurements are performed at 8 sites. These measurements play a crucial role in refining the Shear Wave Velocity Profile Database (VSPDB).
description: This project contains microtremor-based horizontal-to-vertical spectral ratio (mHVSR) data, collected from a series of field surveys conducted at various strong motion stations. The measurements were acquired using 3-component broadband seismometers, with recording durations typically ranging from 30 minutes to 1 hour. mHVSR is a well-established technique for identifying resonant features at sites with substantial impedance contrasts, where the lowest frequency peak in the mHVSR spectrum is often associated with the site’s fundamental frequency. This fundamental frequency is crucial for understanding site-specific seismic behavior and is particularly valuable for seismic hazard assessment and ground motion modeling. The datasets include not only the raw data collected during each survey but also processed outputs such as mean spectral curves, polar curves, Fourier Amplitude Spectra (FAS), and other relevant processing results. These processed data are intended to support further analysis and interpretation, particularly for applications related to site response studies and the characterization of local site conditions. The overall goals of our HVSR research are to develop a publicly accessible database of HVSR data for use in research, to develop effective protocols for analysis and interpretation of HVSR data, and to develop methods for predicting site response conditioned on HVSR data. The database has been established and is available in the United States Community Shear-Wave Velocity (VS) Profile Database (PDB) (https://www.vspdb.org/); the work presented in this doi is contributing to that database. The research presented here was supported by a research gift from the Pacific Gas and Electric (PG&E) Company and University of Southern California. This support is gratefully acknowledged.
DOI: 10.17603/ds2-p7sp-h429
title: Research Experiences for Undergraduates (REU), NHERI 2023: Comparative Study on Cross Laminated Timber (CLT) and Light Wood Framing (LWF)

description: This paper explains and compares cross laminated timber (CLT) and light wood framing (LWF) construction. These construction methods are important because CLT is starting to spread throughout North America while LWF has been the typical method when creating structures. Sustainability, safety, durability, strength, and cost are factors that are taken into account when deciding which method is the best option.
DOI: 10.17603/ds2-29fx-ed12
title: Natural Hazards Research Summit 2022: GreenWall Systems: less steel, more earth for equitable and sustainable hazard resilience

description: This poster discusses a novel type of coastal defense, termed a 'GreenWall'. The proposed research on GreenWalls is inspired by the Doctoral work of the PI on Dual Row Retaining Walls. There is a clear need to re-examine the design philosophy of conventional coastal defenses and breakwaters following the failures caused by multi-hazard events in recent decades (e.g., following the 2011 Tohoku earthquake and tsunami event). 
Previous studies have highlighted that systems that combine soil and structural systems to intentionally utilize the shear strength of the soil can be both resilient to multiple hazards and sustainable in terms of material use and environmental footprints. Results from centrifuge tests and numerical analyses for systems in dry sand inform the fundamental dynamic response of these systems and could inspire a move away from ultimately ambiguous dynamic earth pressure coefficients that have traditionally been used in academia and practice. The same systems founded in liquefiable soils showed a surprising resilience to catastrophic collapse, justified with a ratcheting mechanism that induces co-seismic relative suctions and shear dilation. 
These findings are currently being progressed in the context of testing GreenWall designs using experimental and analytical studies at the Center for Infrastructure, Energy and Space Testing at the University of Colorado Boulder. Open issues, including the convergence of the historically different computational methodologies, experimental methods and especially scaling laws in coastal and geotechnical engineering are explored.
DOI: 10.17603/ds2-ej26-wa59
title: Tsunami Run-up Response Function Based Inversion Model

description: We developed a TRR-INV (Tsunami Run-up Response Function-based inversion) model that can provide probabilistic estimates of a near-field tsunami source and tsunami run-up distribution from a few number of run-up records. This dataset includes the data and code used in developing the application.
DOI: 10.17603/ds2-gsa3-4j39
title: Research Experiences for Undergraduates (REU), NHERI 2022: Soil Compaction for Centrifuge Model Construction

description: The project is about soil compaction and how it contributes to engineering. The data provided helps to look at the differences in soil when using different types of compactors. This data will help give an understanding of what to expect when looking at different types of compacted soil. The project is unique because it emphasizes the use of 3D modeling in order to create compactors, with an audience being students, professors, and other professions that revolve around soil.
DOI: 10.17603/ds2-9dxy-tg94
title: Research Experience for Undergraduates (REU), NHERI 2022: Prediction of Peak Pressure Coefficients Using Higher Order Statistics with Machine Learning

description: This research investigates the prediction of pressure coefficients based on different approach terrain configurations. Machine learning was used to develop an Artificial Neural Network to model these relationships. The data from this project may be used to investigate other relationships that correlate to pressure coefficients. The work conducted in this study is the first of its kind to model the relationship between terrain configurations and pressure coefficients, which will eventually allow the replication of endless testing conditions. The audience of this project is engineers in the field of wind tunnel testing and those who are involved in determining design codes based on wind loads.
DOI: 10.17603/ds2-bdxs-pq18
title: Dynamic Effects of Wind-Induced Vibrations on Curtain Wall Systems

description: This study explores the effects of wind-induced vibrations on curtain wall systems to identify potential causes of damage and suggest viable preventative solutions. Through full-scale simulations at the NHERI Wall of Wind Experimental Facility (WoW EF), test data is gathered for various wind speeds and contact angles by means of strain gauges, accelerometers, and pressure taps spread throughout the model. After employing finite element methods (FEM) to numerically model the curtain wall, the response time history plots extracted from the test data can be used for a two-phase calibration.
DOI: 10.17603/ds2-de5v-ha75
title: Natural Hazards Research Summit 2024: Neural Network Applications in Bridge Seismic Resilience Evaluation

description: Assessing seismic resilience in critical infrastructures like highway bridges is crucial for emergency planning and maintaining network integrity post-hazard events. While machine learning techniques show promise in earthquake engineering, their application to bridge resilience remains under-explored. This study presents the feasibility of applying various neural network architectures to predict the resilience index for a cohort of concrete box-girder bridges with different structural characteristics and exposed to different levels of seismic peak ground acceleration events. The investigation underscores the effectiveness of neural network algorithms in modeling complex relationships between structural characteristics and seismic events, offering valuable contributions to resilience estimation and rapid decision-making processes.
DOI: 10.17603/ds2-smfe-wy17
title: Unidirectional Load Friction Test of PTFE
title: in Seismic protection of artefacts with adhesives and base-isolation

description: This study investigates one of the commonly used methods in New Zealand which is by applying adhesives to anchor small to medium sized artefacts. Guidance is provided to determine the size and number of adhesives required for an artefact to survive design-level earthquake shaking. In addition, for large objects where adhesives alone are insufficient, a simple cost-effective base-isolation platform is proposed to reduce the seismic vulnerability of the artefacts. This platform is designed such that it can be assembled and positioned by museum conservators or private collectors. The adhesive material properties are determined through direct tension and shear experimental tests. The friction properties of the base-isolated substrate are determined through unidirectional quasi-static and cyclic load tests.
description: This test aims to determine the static and dynamic coefficient of friction of Polytetrafluoroethylene (PTFE) on different material surfaces.
DOI: 10.17603/ds2-txry-v075
title: Research Design Table—CONVERGE Extreme Events Research Check Sheets Series

description: This publication is intended to assist investigators to ensure that they have addressed a variety of research design issues that often emerge in the proposal writing and review stages for social science studies. Specifically, it raises a number of questions to help investigators consider how they will frame and articulate their research questions, study timing, sampling, data collection and analysis plans, team composition, and ethical considerations. 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/ds2-56xc-tn90
title: Natural Hazards Research Summit 2022: Reinforcing coastal resiliency: how advancements in machine learning can guide ongoing efforts

description: Among the most hazard-prone regions today are coastlines, where the population density and the lack of preventive actions against climate change has created multi-faceted challenges. In order to offer holistic solutions that are tailored to each region, one cannot rely simply on historical data, which might be sparse or insufficient. Breakthroughs in simulating natural phenomena the past decades have allowed the more in-depth investigation of various hypothetical scenarios using high fidelity models. Although such tools are of extreme detail, they tend to be computationally intensive, preventing the repetition of multiple analyses in a risk assessment setting. Surrogate models are data driven tools, that are able to develop mathematical approximations between the input and the output of complex and expensive numerical models. They are able to maintain similar accuracy to the high fidelity model they try to emulate, but at a significantly lower computational cost. Such tools have been proven particularly useful in coastal hazard assessment applications, especially for predicting storm surge for large regions of interest, taking into account sea level rise, complex local geomorphology and even the spatio-temporal surge evolution. Future endeavors involving such tools, are aiming to incorporate the tidal component/precipitation in those predictions, investigating additionally the intensification of storms and how available databases can be enriched towards this direction.
DOI: 10.17603/ds2-qkxb-pa58
title: ISROC Dataset for: Characteristics and hydrodynamics of boulders transported by storm waves at Kudaka Island, Japan
title: in Inundation Signatures on Rocky Coastlines (ISROC) Global Coastal Boulder Deposits Datasets Version 1

description: This document contains standardized data as an Excel and NC file and explanatory notes for "Characteristics and hydrodynamics of boulders transported by storm waves at Kudaka Island, Japan." This study focuses on 6 storm wave coastal boulders on Kudaka Island. The study uses the boulder's exponential fining trend shoreward to determine the movement of the boulders and the characteristics of the storm waves affecting them.
description: This project is a collection of datasets on studies about coastal boulder deposits worldwide. Each document is a unique dataset that contains data from a published study. The document's name reflects the name of the associated paper, and all authors of papers are given credit in the respective document. Each dataset's data is standardized into an ISROC-formatted Excel and NC File. Also, every dataset has explanatory notes, which contain a data dictionary explaining data parameters and appropriate units, Some datasets have the raw data given to ISROC by the paper's authors. By creating a database in the public domain, ISROC hopes to promote academic collaboration in the field. ISROC, an NSF-funded research network, funds this project.
DOI: 10.17603/ds2-02jz-3v08
title: Atterberg limits
title: in Characterization and Geotechnical Properties of Wildfire Ashes

description: This project summarizes the geotechnical engineering properties of eight samples of wildfire ash sampled from three different wildfire sites in central and southern California. This data can be used in conjunction with data collected from others to provide a database of the physical, chemical, hydrological, and engineering properties of wildfire ashes. Extensive engineering testing of wildfire ashes is not readily available in literature, so this work will supplement the supply currently available. This work would be information and educational for those researching wildfire ashes, fire-exposed slopes, carbonate-rich soils, and manmade soils, including other types of ash. This data can be reused by those who would like reference data for further testing on wildfire ashes and for those who require reference data on soil engineering properties.
description: Atterberg limit testing was performed on ash samples sieved over the No. 40 sieve (ASTM D4318 2010). Samples could not be rolled into a thread or molded appropriately for the plastic limit thread test. Instead, the maximum and minimum blow counts from the Casagrande cup test were used to generalize the plasticity index of the samples.
DOI: 10.17603/ds2-4rf2-bj36
title: Shake Table Damage Detection Using Terrestrial Laser Scanning Techniques
title: in RAPID/Collaborative Research: Japan-U.S. Collaboration on the Seismic Resilience of Wood-frame Building Systems

description: Two full scale wood frame buildings were tested under seismic loading via shake table tests. This project focused on lidar scanner measurements before and after each test shaking intensity to be able to identify damage patterns and create 3D virtual models of the structures in different phases of testing. 

The data shared herein can be use by other researchers to further assess damage models or even validate numerical models against experimental data.

The metadata includes a scan position registration report that is required to understand the accuracy of the related pointcloud data (.las). The report identifies the “registration accuracy”, that is the accuracy of the registration of individual scan positions, or how well individual scan positions fit with one another. The registration accuracy is independent of the instrument accuracy (See “Sensor Information| Setting of Lidar Scanners”). The overall accuracy of each pointcloud should be considered as either, A) the largest registration error reported in the metadata, or B) the “Instrument Accuracy”, whichever is largest. Generally, the registration accuracy will be larger than the instrument accuracy.
description: This project presents the application of modern survey techniques in collecting damage data of full-scale shake table tests in order to preserve their time-sensitive outcomes for future researchers. This study utilized modern instruments, especially Light Detection and Ranging (LiDAR) scanners, to collect damage data from shake table experiments of two full-scale wood residential buildings tested at the E-Defense facilities in Miki, Japan. This study utilized close- and long-range LiDAR scanners to collect comprehensive 3D point clouds of the interior and exterior of the buildings after each test day, as well as a number of times in-between tests. Based on lessons learned, a survey protocol is proposed to be followed by researchers planning to conduct data collection from shake table tests using modern instrumentation in the future. The protocol includes the necessary actions prior, during, and after the experiments. In addition, advantages of the LiDAR scans over ordinary visual inspections and their capabilities are discussed by demonstrating a number of examples of the application of the collected LiDAR scans to detect and quantify damage in structural and nonstructural components of the two buildings. The results show the efficacy of collecting time-sensitive data using modern techniques. This data presented/published here in can be used for damage detection and structural response evaluation of similar buildings by other researcher or even for validation of numerical models.