Andrew J Graettinger
Biographic Data
| ID | 9720939 |
|---|---|
| NAME | Andrew J Graettinger |
| GIVEN NAMES | Andrew J |
| FAMILY NAME | Graettinger |
| SIGNATURE | GRAETTINGER A J |
| AFFILIATIONS | University of Wisconsin–Milwaukee |
| ORCID | 0000-0002-1858-2307 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 0 |
Discrete-Outcome Analysis of Tornado Damage Following the 2011 Tuscaloosa, Alabama, Tornado
Ground-truth measurements of damage caused by natural disasters are routinely used to determine which factors of the natural, built, and social environment contribute to losses from these events. Process-based models, which are based on structural design and probability theory, are often used in engineering risk analysis to predict damage and subsequent losses from these events, but empirical modeling can effectively aid in capturing the partial …
Community Resilience-Focused Technical Investigation of the 2016 Lumberton, North Carolina, Flood
In early October 2016, Hurricane Matthew crossed North Carolina as a Category 1 storm, with some areas receiving 0.38–0.46 m (15–18 in.) of rainfall on already saturated soil. The NIST-funded Center for Risk-Based Community Resilience Planning teamed with researchers from NIST’s Engineering Laboratory (Disaster and Failure Studies Program, Community Resilience Group, and the Applied Economics Office) to conduct a field study focused on the impact…
No prominent works on this page.
Discrete-Outcome Analysis of Tornado Damage Following the 2011 Tuscaloosa, Alabama, Tornado
Ground-truth measurements of damage caused by natural disasters are routinely used to determine which factors of the natural, built, and social environment contribute to losses from these events. Process-based models, which are based on structural design and probability theory, are often used in engineering risk analysis to predict damage and subsequent losses from these events, but empirical modeling can effectively aid in capturing the partial …
Community Resilience-Focused Technical Investigation of the 2016 Lumberton, North Carolina, Flood
In early October 2016, Hurricane Matthew crossed North Carolina as a Category 1 storm, with some areas receiving 0.38–0.46 m (15–18 in.) of rainfall on already saturated soil. The NIST-funded Center for Risk-Based Community Resilience Planning teamed with researchers from NIST’s Engineering Laboratory (Disaster and Failure Studies Program, Community Resilience Group, and the Applied Economics Office) to conduct a field study focused on the impact…
Engineering (2 works) · Environmental Science (2 works) · Flood Risk Assessment and Management (2 works) · Geography (2 works) · Built environment (1 work) · Civil engineering (1 work) · Community resilience (1 work) · Computer Science (1 work) · Disaster Management and Resilience (1 work) · Environmental planning (1 work)