Kurt Gurley
University of Florida
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Kurt Gurley.
Natural Hazards Review | 2015
G. L. Pita; Jean-Paul Pinelli; Kurt Gurley; Judith Mitrani-Reiser
AbstractThis paper presents a comprehensive review of methods to assess building vulnerability for hurricane catastrophe models. The review identified five main types of assessment approaches judging by the underlying methodology: past-loss data, enhanced damage data, heuristic, physics, and simulation. The applicability of past-loss data-only vulnerability methods proved insufficient for the diversity of situations insurance companies faced. Therefore, modelers complemented this method with engineering and meteorology expert knowledge; these are the enhanced-data models. Expert opinion and subjective probabilities drive the heuristic models; these were short lived in the United States, but are still used when data are scarce. Component-based methods were developed as a more realistic alternative to enhanced-data models by assessing vulnerability within an engineering framework complemented with expert opinion. Simulation models enhanced the physical models with a probabilistic simulation of the wind-stru...
Natural Hazards Review | 2014
Boback Bob Torkian; Jean-Paul Pinelli; Kurt Gurley; Shahid Hamid
AbstractThe hurricanes of recent years have caused many insurers to raise their premiums in response to increased losses. In the long-term, the most effective solution to reduce damage and insurance costs is to apply mitigation techniques. This paper presents a methodology for evaluating the effectiveness of various mitigation measures in reducing wind storm losses to residential buildings. The individual mitigations were combined into different sets. These sets of mitigations were applied to typical timber box and masonry residential structures of different ages and quality of construction (from weak pre-1970 to stronger post-2002 construction). In each case, a detailed cost analysis of the unmitigated and mitigated building was performed, and the relative cost-effectiveness of mitigation was assessed through comparisons of the results of portfolio analyses with and without mitigation. The mitigation cost-effectiveness study includes component vulnerabilities from Monte Carlo simulation, overall building...
First International Symposium on Uncertainty Modeling and Analysis and Management (ICVRAM 2011); and Fifth International Symposium on Uncertainty Modeling and Anaylsis (ISUMA) | 2011
G. L. Pita; Jean-Paul Pinelli; Kurt Gurley; Johann Weekes; Judith Mitrani-Reiser
Regional wind loss predictions depend on vulnerability curves. A state of the art approach for developing the vulnerability curves is presented in the paper. It is based on engineering models that estimate the building damage caused by wind pressures, debris impact, and water penetration. This approach is a substantial improvement over traditional approaches, which derive vulnerability curves for different kind of buildings through curve fitting of historical insurance loss data. This paper describes the engineering model used to develop vulnerability curves for commercialresidential buildings in the Florida Public Hurricane Loss Model.
Journal of Structural Engineering-asce | 2017
Mohammad Baradaranshoraka; Jean-Paul Pinelli; Kurt Gurley; Xinlai Peng; Mingwei Zhao
AbstractAnnualized hurricane-related losses in the United States are in the billions of dollars. The majority of the coastal population lives in buildings prone to hurricanes, which could result in...
ATC & SEI Conference on Advances in Hurricane Engineering 2012 | 2012
Jean-Paul Pinelli; T. Johnson; G. L. Pita; Kurt Gurley
This paper describes how modelers of the Florida Public Hurricane Loss Model (FPHLM) account for and implement various roofing characteristics that reflect the historical building practices and code enforcement in Florida. The life cycle of roofing structural elements, particularly the roof cover, are considered by using an algorithm to estimate whether or not a structure has been retrofitted based on the original year built. The paper will discuss the role of building practices and life cycles of roofing components and their use in vulnerability models as well as discuss the influence of roof retrofits on the vulnerabilities of typical personal residential structures.
First International Symposium on Uncertainty Modeling and Analysis and Management (ICVRAM 2011); and Fifth International Symposium on Uncertainty Modeling and Anaylsis (ISUMA) | 2011
Boback Bob Torkian; Jean-Paul Pinelli; Kurt Gurley
This article presents a survey which was carried out to identify the most prevalent residential building types, their characteristics and their distribution in the state of Florida. The databases provided by county property tax appraisers were used for the survey. Detailed statistics on different building components are presented along with an analysis of their correlation to the year built of the structures. The results of the survey provided a basis for the generation of different vulnerability matrices in different regions of Florida. The survey, the resulting statistical analysis, and the weighting process of the vulnerability matrices are discussed.
Archive | 2004
Jean-Paul Pinelli; Josh Murphree; Chelakara Subramanian; Kurt Gurley; Anne Cope; Shahid Hamid; Sneh Gulati
The paper presents a methodology to predict hurricane insurance losses for the State of Florida on an annualized basis and for predefined scenarios. Although several loss prediction commercial products exist in the market, this is one of the first public models entirely accessible for scrutiny to the scientific community. The model incorporates the latest state of the art techniques in hurricane prediction, and vulnerability modeling based on engineering criteria. Although the model was developed for Florida, it is applicable to any hurricane prone region. The methodology can also be extended to other types of hazards.
Journal of Structural Engineering-asce | 2004
Jean-Paul Pinelli; Emil Simiu; Kurt Gurley; Chelakara Subramanian; Liang Zhang; Anne Cope; James J. Filliben; Shahid Hamid
Statistical Methodology | 2010
Shahid Hamid; B. M. Golam Kibria; Sneh Gulati; Mark D. Powell; Bachir Annane; Steve Cocke; Jean-Paul Pinelli; Kurt Gurley; Shu-Ching Chen
Natural Hazards Review | 2011
Shahid Hamid; Jean-Paul Pinelli; Shu-Ching Chen; Kurt Gurley