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7 results for “Hurricane Structure”

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edi56/100

Mangrove Coast Collaborative Project, Post-hurricane Irma mangrove forest structure data, Rookery Bay NERR, February 2022 - March 2023

The dataset describes the structure, composition, and condition of mangrove forests in Rookery Bay National Estuarine Research Reserve (NERR) assessed Feb 2022 - Mar 2023, approximately 5 years post Hurricane Irma (2017) and concurrent with Hurricane Ian (Sep 2022). The dataset includes information on each stem greater than or equal to 1 cm DBH (diameter at breast height) rooted within 69 100 m2 circular plots. Information collected includes site ID, location, species, DBH, status (live or dead), damage associated with the hurricane, presence/absence of regrowth, presence/absence of adventitious roots, whether or not stem is part of a multi-stemmed individual, and the canopy conditions (whether the tree has a canopy or is only sprouting at the base of the tree or trunk). This dataset is associated with the Mangrove Coast Collaborative project (2020 - 2024).

openCC (other)Sep 2025View details →
edi56/100

Mangrove Coast Collaborative Project, Post-hurricane Maria mangrove forest structure data, Jobos Bay NERR, March 2022 - August 2022

The dataset describes the structure, composition, and condition of mangrove forests in Jobos Bay National Estuarine Research Reserve (NERR) assessed approximately 5 years after disturbance from Hurricane Maria (2017). The dataset includes information on each stem greater than or equal to 1 cm DBH (diameter at breast height) rooted within 64 100 m2 circular plots. Information collected includes site ID, location, species, DBH, status (live or dead), damage associated with the hurricane, presence/absence of regrowth, presence/absence of adventitious roots, whether or not stem is part of a multi-stemmed individual, and the canopy conditions (whether the stem has a leafed canopy or is only sprouting at the base if live). This dataset is associated with the Mangrove Coast Collaborative project (2020 - 2024).

openCC (other)Sep 2025View details →
zenodo36/100

The Impact of Hurricane Harvey on Pavement Structures in the South East Texas and South West Louisiana

<p>Corresponding data set for Tran-SET Project No. 18PUTA02. Abstract of the final report is stated below for reference:</p> <p>&quot;This study developed a methodology to estimate the damage caused by flooding, such that caused by Hurricane Harvey, on a road or street network. The flooded street or pavement sections are identified using GIS flood maps with street GIS maps used for pavement management systems (PMS) by cities or state authorities. Then the damage caused by flooding directly through the increase moisture in foundation layers or indirectly due to the increase heavy traffic during the relief effort is estimated. An example Excel macro was created to illustrate the estimation process. The methodology estimates the increase in rehabilitation costs since the flooding imposes that many rehabilitation works must be done earlier than anticipated before the flooding. The methodology also estimated the increase in fuel consumption caused by the increased in pavement roughness if the rehabilitation works are done when anticipated before the flooding. The methodology and the Excel macro can also be used to identify the pavement structures with better resilience to the flooding by grouping sections based on the flooding duration (no flooding, single and multiple day flooding) and on design features such as pavement type, functional class, age or time from the most recent resurfacing or reconstruction, subgrade soil type, traffic volume, layer thickness.&quot;</p>

opencc-by-4.0Sep 2019View details →
zenodo36/100

Data Supporting "Air-Sea Momentum Exchange with Explicit Wind-Wave-Current Coupling and Effects on Hurricane Structure and Impacts"

<p>This dataset produced the figures for the Air-Sea Momentum Exchange with Explicit Wind-Wave-Current Coupling and Effects on Hurricane Structure and Impacts Manusrcipt.</p>

opencc-by-4.0Jun 2024View details →
dryad32/100

Data from: Immediate impact of a hurricane on the structure of a tropical butterfly community

More intense and frequent hurricanes may lead to long-lasting effects to tropical ecosystems. Here we describe the immediate impact on the butterfly community of a lowland forest in Belize, following Hurricane Earl. Species richness and abundance increased post-hurricane, likely driven by convergence of the organisation between the canopy and understory communities.

opencc-zeroDec 2017View details →
dryad32/100

Data from: Immediate impact of a hurricane on the structure of a tropical butterfly community

Open the record for dataset details and reuse information.

publicFeb 2018View details →
zenodo28/100

Structural Vulnerability of Coastal Bridges Under Extreme Hurricane Conditions

<p>Corresponding data set for Tran-SET Project No. 18STTSA04. Abstract of the final report is stated below for reference:</p> <p>&quot;This work presents the results of a numerical study evaluating the response of coastal bridges due to hurricane-induced waves. The analyses were conducted using the Coupled Eulerian-Lagrangian (CEL) approach, available on the commercial finite element software Abaqus, which allows modeling the interaction between water and the bridge. The work concentrated on (1) establishing an approach for modeling the desired wave characteristics (i.e., wave height, and frequency) within the CEL simulation, (2) conducting simulations using actual bridge dimensions of historically damaged bridges, (3) analyzing a range of foundation flexibilities to determine its effect on the uplift and shear forces acting on the superstructure, and (4) comparing results simulations to AASHTO equations that estimate wave forces acting on coastal bridges. The numerical study revolved around two major highway bridges damaged along the U.S Gulf Coast during hurricane Katrina in 2005, (a) the U.S 90 highway bridge over Biloxi Bay and (b) the US. 90 St. Louis-Bay Bridge. The water level elevation was defined at the bottom of the superstructure as post-Katrina investigations revealed that this was a common characteristic for damaged bridges. The analysis revealed that (a) bridge models with flexible foundations provide better force design estimates than models with rigid supports, (b) the force demands are presumably amplified when the natural frequency of the bridge coincides with that of the traveling waves, and (c) CEL force estimates show large peak magnitudes during wave impacts that exceed AASHTO estimates. Further research is required to determine if these peaks are numerical artifacts or a concern for connection design.&quot;</p>

opencc-by-4.0Jul 2019View details →

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International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

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OpenNeuro

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neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record