ORIGINAL RESEARCH
Accepted on 26 May 2025
A Decade of DesignSafe: Enabling Open Science in Natural Hazards
doi 10.3389/fbuil.2025.1594375
- 101 views
- Frontiers in Built Environment
- Coastal and Offshore Engineering
- Research Topics
- NHERI 2015-2025: A Decade of Discovery in Natural Hazards Engineering
NHERI 2015-2025: A Decade of Discovery in Natural Hazards Engineering
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Articles
ORIGINAL RESEARCH
Accepted on 16 May 2025
Successful Coordination of the Distributed, Natural Hazards Engineering Research Infrastructure (NHERI)
doi 10.3389/fbuil.2025.1589067
- 133 views
ORIGINAL RESEARCH
Accepted on 14 May 2025
A Unified Framework for Post-disaster Hazard and Structural Assessment Data Collection Across Hazards and Infrastructure Typologies
doi 10.3389/fbuil.2025.1546616
- 259 views
REVIEW
Published on 23 Apr 2025
Multi-degree of freedom shake table testing of large-scale structural and geotechnical systems with NHERI-UCSD LHPOST6
doi 10.3389/fbuil.2025.1573390
- 669 views
ORIGINAL RESEARCH
Published on 19 Mar 2025
Recent developments and discoveries in natural hazards mitigation research at the NHERI Lehigh Experimental Facility
doi 10.3389/fbuil.2025.1567729
- 591 views
ORIGINAL RESEARCH
Published on 21 Feb 2025
Wind load impact on tall building facades: damage observations during severe wind events and wind tunnel testing
doi 10.3389/fbuil.2024.1514523
- 4,197 views
ORIGINAL RESEARCH
Published on 17 Feb 2025
An ethnographic case study of undergraduate researchers in natural hazards engineering
doi 10.3389/fbuil.2025.1535761
- 365 views
ORIGINAL RESEARCH
Published on 23 Jan 2025
NHERI education and community outreach: longitudinal, educational outcomes of a coordinated, distributed network
doi 10.3389/fbuil.2025.1512507
- 355 views
ORIGINAL RESEARCH
Published on 07 Jan 2025
NHERI@UTexas experimental facility with large-scale mobile shakers for field studies: a decade of discovery in natural hazards engineering
doi 10.3389/fbuil.2024.1524030
- 472 views
ORIGINAL RESEARCH
Published on 12 Dec 2024
Automated extraction and summarization of wind disaster data using deep learning models, with extended applications to seismic events
doi 10.3389/fbuil.2024.1485388
- 710 views
