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John W. van de Lindt

Researcher at Colorado State University

Publications -  290
Citations -  5511

John W. van de Lindt is an academic researcher from Colorado State University. The author has contributed to research in topics: Shear wall & Seismic analysis. The author has an hindex of 34, co-authored 271 publications receiving 4074 citations. Previous affiliations of John W. van de Lindt include Oregon State University & Michigan Technological University.

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Damage Study and Future Direction for Structural Design Following the Tuscaloosa Tornado of 2011

TL;DR: David O. Prevatt, Ph.D., University of Alabama, Tuscaloosa, AL William Coulbourne, P.E., Applied Technology Council, Rehoboth Beach, DE Rakesh Gupta et al. as discussed by the authors, University of Florida, Gainesville, FL John W. van de Lindt and Andrew Graettinger.
Journal ArticleDOI

Minimal Building Flood Fragility and Loss Function Portfolio for Resilience Analysis at the Community Level

Omar M. Nofal, +1 more
- 13 Aug 2020 - 
TL;DR: A method that allows the development of building fragility and building loss functions is articulated and applied to develop an archetype portfolio that can be used to model buildings in a typical community.
Book ChapterDOI

Force Modification Factors for CLT Structures for NBCC

TL;DR: Results showed that an Rd-factor of 2.0 is appropriate for the building studied, and suitable ductility-based force modification factors for seismic design of CLT buildings in the National Building Code of Canada (NBCC).
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Performance-Based Tsunami Engineering for Risk Assessment of Structures Subjected to Multi-Hazards: Tsunami following Earthquake

TL;DR: Tsunamis are low-probability high-consequence events, usually caused by an earthquake in the ocean and can result in high casualty rates and billions of dollars in damage.
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Loss Analysis for Wood Frame Buildings during Hurricanes. I: Structure and Hazard Modeling

TL;DR: In this paper, the structural and hazard modeling for a passing hurricane is explained and demonstrated, and a hazard model is developed using a combination of existing wind tunnel data and a rainwater intrusion model.