The need to predict hurricane-induced losses for $3.6 trillion worth of existing insured structures exposed to potential hurricane devastation in the state of Florida has prompted the Florida Department of Insurance (FDOI) to charge a group of researchers with the task of developing a public hurricane loss projection model. This is a joint effort between Florida Tech, Florida International University, University of Florida, Florida State University, University of Miami, University of Notre Dame, NOAA and NIST. Florida Tech and the University of Florida are responsible for the development of the engineering or vulnerability module of the model. It is a work in progress.
The FPHLM is administered through the International Hurricane Research Center at FIU - Project manager: Shahid Hamid http://www.cis.fiu.edu/hurricaneloss/index.html.
The FPHLM has been certified by the Florida Commission on Hurricane Loss Methodology (http://www.sbafla.com/methodology/) in 2007, 2008, and 2009, 2011, 2013.
The basic objective of the model is to produce good estimates of hurricane losses and therefore help determine actuarially sound pricing for homeowner insurance that is fair to both homeowners and to the insurance companies.
|2013-2014||Enhancement of the Florida Public Hurricane Loss Model with Storm Surge: Funded by the Florida Department of Financial Services, through the International Hurricane Research Center at FIU. Dr. Pinelli leads the engineering team.|
|2010-2012||Development of Test-Based Data on Hurricane-Induced Building Interior, Utility, and Contents Damage for Improved Risk Prediction and Mapping. Funded by the Florida Sea Grant Program.|
|2009-2012||A Model to Evaluate the Benefit and Cost of Hurricane Mitigation Measures: Vulnerability Component. Funded by the Center of Excellence for Hurricane Damage Mitigation & Product Development, through the International Hurricane Research Center at FIU.|
|2001-2014||Florida Public Hurricane Loss Model: Funded by the Florida Department of Financial Services, through the International Hurricane Research Center at FIU. Dr. Pinelli leads the engineering team, involving several institutions, for the development and maintenance of the vulnerability module, and mitigation studies.|
|2004-2006||Risk Versus Mitigation Measures: Quantifying Residential Vulnerability to Hurricane Winds and Evaluating the Cost Effectiveness of Retrofits Damage Mitigation. Funded by the Florida Sea Grant College Program. Joint proposal with the University of Florida.|
Abstract: The need to predict hurricane-induced losses for $1.5 trillion worth of existing structures exposed to potential hurricane devastation in the state of Florida has prompted the Florida Department of Insurance (FDOI) to charge a group of researchers to develop a Public Hurricane Loss Projection Model Project.
The Project calls for the efforts of several functional teams: A meteorological team is in charge of developing a hurricane wind model; an engineering team develops the building vulnerability and exposure model; an actuarial team translates the building physical damage to insurance loss and a computer team builds a user-friendly and stable computer platform. This thesis is a part of the work of the engineering team.
The thesis focuses on single-family residential buildings and manufactured homes. It covers three topics. First, the development of a unique component approach vulnerability model is introduced. Second, the thesis presents the results of a building exposure study, namely, the determination of the most common structural types for four Florida regions. Finally, the thesis proposes a cost calculation model combining the results of the previous two topics.
The component approach vulnerability model is built upon the following procedure. Five basic damage modes, i.e. breakage of openings, loss of roof cover; loss of roof sheathing; roof to wall connection failure, and wall failure, were defined for a generic residential structural type. Each of these five damage modes was assigned four levels of intensity: no damage, light, medium and heavy damage. All these partial damage modes can then be combined in 217 possible damage states. For each of these combined damage states, their probability of occurrence for different wind speed intervals can be estimated though Monte Carlo simulations, for each identified structural type. The results are damage or vulnerability matrices for each particular structural type.
The selection of the particular structural types is the result of the exposure study presented here. To study the building exposure of Florida, the author analyzed nine Florida counties’ property tax appraiser databases. As a result, for those nine counties, the thesis presents the detailed distributions of major building characteristics: roof type; roof cover; exterior wall structure, area, and year built. The results are then used to define the most common structural types and their probability of occurrence over four Florida regions: North, Central, Southeast, and the Keys.
The results of the vulnerability modeling and building exposure studies are combined in a cost estimation procedure. Based on an estimate of the cost associated with each damage states, two types of damage can be estimated: the average annual cost of hurricane induced damage for a given return period; or the damage cost for a given hurricane scenario.
Abstract: Hurricane force winds pose a potentially devastating threat to the $1.5 trillion dollars of existing real estate in the state of Florida. With rapidly increasing populations in coastal regions where this risk is highest, the need for insurance companies operating within the state to predict future losses from these events is critical. These circumstances prompted the Florida Department of Financial Services (FDFS) to request that a group of researchers develop a public hurricane loss projection model to estimate damage to residential structures when subject to high winds associated with hurricanes. Several models of this sort exist however almost all are developed for insurance companies for ratemaking purposes and being proprietary models the public has no access to the results which they produce.
The complete risk assessment model is built from several distinct parts including: the wind field model, the exposure study, the vulnerability model, actuarial components, and the computer platform. The work presented in this report deals primarily with the development of the vulnerability model and its integration with the other components.
Rather than using regression analysis of claims data to define the vulnerability of homes like other models, this vulnerability model uses a component approach that explicitly considers the resistance capacities of each component of a home and the wind forces produced at increments of wind speed to define damage. Variability in both the resistance capacities and wind forces are modeled using Monte Carlo simulation techniques. Monte Carlo simulation models are developed based upon what were determined from an exposure study to be the typical structural types in each region of the state.
The Monte Carlo simulations only model physical damage to the major components of each home type. From the modeled damages to these components damage to the remainder of the home (the interior and utilities), likely contents damage, and repair times are extrapolated. The cost of repairing all damage is calculated based upon typical repair costs, defined by various costing resources, for each structural type. A separate model is also developed to predict damages to appurtenant structures. The repair cost predictions are organized in vulnerability matrices, which define the probability of any increment of damage given a particular wind speed, or the probability of contents and additional living expense damage given an increment of structural damage.
These damage predictions are validated using historical claims data from recent Florida hurricanes and inspections of structures damaged during the 2004 hurricane season.
Actuarial considerations are applied to the vulnerability model predictions to define insured losses. All components are integrated together to form the complete insurance loss projection model, which can be used to simulate historical or hypothetical storm events or to predict average annual insured losses to a home covered by an insurance policy, a zip code, region, the entire state, or complete insurance portfolio file.
Abstract: Hurricanes left billions of dollars in damage in Florida, in 2004 and 2005. To minimize these losses there is a need to create a reliable model that can predict and project economic insured losses for these natural disasters. To address that need, the Florida Department of Financial Services (FDFS) commissioned a group of researchers to develop the Florida Public Hurricane Loss Projection Model (FPHLPM), a computer model used to predict both scenario and annual expected insured losses to residential structures subject to high winds associated with hurricanes. This report describes the latest round of upgrades of the vulnerability component of the FPHLPM.
First, the existing model was modified to predict more damage at low wind speeds. Second, the existing model was replaced by three new models; a weak, a medium, and a strong model, which better reflect the quality of construction of the average home by considering the evolution of building codes and their enforcement over time. Third, sliding and overturning models of manufactured homes were improved in the new model.
The 2004 hurricane insurance provided a wealth of claim data, used to validate and calibrate the FPHLPM. First, the consistency and validity of the data itself was investigated, and the associated wind speed data was sought from NOAA. The results from the model were then compared to the claim data for hurricanes Charley, Frances, and Ivan. The comparisons were done for the different structural types, for the different age categories, and for different insurance companies. They included comparisons of aggregated losses and of vulnerability curves. The comparisons suffered from the fact that the actual wind data that caused the damage was not always available, and there was some unknowns regarding the true nature of coverage of many insurance policies.
However, initial comparisons did show that building, appurtenant and ALE damage needed to be increased, while contents damage needed to be decreased. In order to calibrate the model, the equations defining the interior damage were adjusted to reflect more building damage. In particular, the relationships between sheathing, roof cover, and gable ends, in one hand, and interior damage in the other hand were adjusted, in order to induce significant increases in the model building damage. Similarly, contents damage was decreased thanks to a new relationship with interior damage. The new equations were obtained by trial and error, keeping in mind the physics of the problem.
In conclusion, the FPHLPM seems to be under predicting building (i.e. structure) losses, over predicting contents losses, and under predicting appurtenant and ALE losses. As a result, the engineering model was recalibrated, and further modifications are under way. These efforts are carried out in close collaboration with the meteorological and actuarial teams who also need to further refine their models. The whole process revealed the difficulties inherent into the validation of any risk analysis model. First, it is difficult to obtain relevant unbiased loss data. Hazard data is even more difficult to obtain due to a lack of actual measurements on the ground, and therefore, the actual relationship between hazard and loss is uncertain. This makes the validation of any loss model a difficult task, which needs to be continuously updated.
Abstract: Historically, hurricanes have presented a constant threat to the State of Florida. The cost of the wind induced destruction affects individual home owners, the insurance industry and the State in general. Mitigation of this hurricane damage is therefore a critical issue in the State, and given the limited resources available, it is important to define which mitigation measures would be more cost effective for home owners. Consequently, the Florida Sea Grant Consortium has funded research at Florida Tech and the University of Florida to investigate the cost effectiveness of different mitigation measures for residential structures. This thesis presents the result of this work.
The thesis analyses the cost effectiveness of various combinations of mitigation measures for different types of structure of different age and quality. The work was possible thanks to the utilization of the Florida Public Hurricane Loss Projection Model (FPHLPM), a hurricane risk analysis model previously developed with the joint collaboration of Florida Tech, and the University of Florida, among others, under the leadership of Florida International University. This is the first formal attempt to present a full-scale model that dictates which mitigation measures –applied together- will result in the highest economic benefit for specific regions in the State of Florida.
Different sets of mitigation measures were investigated that combined improved roofing materials, improved roof to wall connections, and different kind of opening protection. This mitigation measures were applied to typical timber box and masonry residential structures of different age 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. The necessary changes in the vulnerability matrices of the FPHLPM were implemented in order to model the resulting mitigated structures.
The FPHLPM was then used to get the expected annual losses (EAL) for each building type, mitigated and unmitigated, for each zip code in Florida. The EAL can de defined as the long term average annual loss at any given location. The difference between the unmitigated EAL and the mitigated EAL was defined as the benefit of mitigation. The cost of mitigation was then transformed into an annuity, and the variation of (benefit – cost) for each zip code was color mapped for the entire State of Florida, for every building type investigated.
The resulting maps showed that for most mitigation measures and for most structural types, the mitigation is really cost effective only in the Southeast region of Florida. These preliminary conclusions did not take into account insurance deductible and limits, nor possible tax credits or cash incentives like insurance premium reductions. The study also showed that the results have a high degree of uncertainty attached to the definition of the actual costs, the interest rate, and the inflation rate. These variables could have a significant effect on the cost effectiveness of certain mitigation measures, and need to be further investigated.
Abstract: Insurance and re-insurance companies as well as insurance regulators rely upon catastrophe models to project insured losses caused by hurricanes. Catastrophe models, such as the Florida Public Hurricane Loss Model (FPHLM), simulate the passage of many hurricanes—with probabilistic return periods and physical features—over an insurance portfolio of buildings to estimate the building damage which is later translated into monetary loss. These models have three components: atmospheric, vulnerability and actuarial. This dissertation focuses on the vulnerability component of the FPHLM. Specifically, the dissertation proposes two novel methodologies to assess the vulnerability of commercial-residential buildings (low-rise and mid/high-rise buildings).
The main contribution of the proposed vulnerability model for low-rise buildings lies in the interior damage estimation model. For the vast majority of buildings the value of their interior (partitions, fixed furniture, ceilings, doors, flooring, finishing, etc.) approaches or surpasses that of the exterior (i.e. the building envelope). To date, most of the interior vulnerability models reported in the technical literature are based either on expert-opinion or claim data model fitting. This dissertation proposes to estimate the building interior damage caused by a hurricane with a physical model of rain penetration and water propagation. First, the rain impinging against a building is estimated based on the simulation of the co-occurrence of wind and rain. Then, the model computes the water penetration through the breached components of the envelope. Finally, the water accumulated inside the building is translated into interior damage.
The mid/high-rise buildings have complex geometries which make them intractable for the kind of holistic vulnerability model tailored for low-rise buildings. Consequently, this dissertation proposes a modular methodology that is flexible enough to account for virtually any building geometry. Low-rise vulnerability model produces vulnerability curves for different kind of typical buildings which are loaded by the catastrophe model to assess a building damage given a wind speed. This is not possible in mid/high-rise buildings because they are subject to a wind profile and also due to their geometry. Consequently, this model evaluates the vulnerability of each particular building in an insurance portfolio during the portfolio analysis.
The dissertation also presents a comprehensive survey of the commercial-residential building stock in Florida from county tax appraiser databases. The results of the survey were used to characterize the building inventory in Florida, and define generic models for low-rise buildings and mid/high-rise apartment units. The resulting statistics are also used to make up for missing information into the insurance portfolios. In addition, since most tax appraiser databases lack some information, a methodology is proposed to populate missing information using the Bayesian Belief Networks and Classification and Regression Trees techniques.
In summary this dissertation contributes with: a thorough account of the vulnerability models of low-rise and mid/high-rise buildings, a physically-based approach to account for the most influential damage type—i.e. interior damage—, a modular approach to assess the vulnerability of mid/high-rise buildings, an extensive building survey, and a methodology to populate incomplete buildings-features databases.
Abstract: In the state of Florida, hurricanes represent the greatest natural risk to the insured building stock and have caused billions of dollars in damage over the last 20 years. Catastrophe models (CAT) predict the economic insured losses caused by these natural disasters. For that purpose, the Florida Office of Insurance Regulation (OIR) commissioned a group of researchers to develop the Florida Public Hurricane Loss Model (FPHLM), a computer model used to predict both scenario and annual expected insured losses to residential structures subject to hurricanes.
The FPHLM is constantly evolving according to the state of the art of catastrophe modeling, and also in response to the requirements of the Florida Commission on Hurricane Risk Projection Methodology. This thesis reports some of the latest advances in the development of the FPHLM. In particular, in version 4, the FPHLM engineering team expanded the capabilities of the personal residential component of the FPHLM to include additional building model types which represent more accurately the building practices and code enforcement history in the state of Florida. In addition to the new building models, a mapping tool was also created to match each policy in an insurance portfolio with the most appropriate vulnerability matrix from within the library of vulnerability matrices of the FPHLM.
Finally, up to version 3.1, the FPHLM covered only personal residential buildings. Version 4 of the FHPLM includes a new commercial residential low rise building vulnerability model. The commercial residential model incorporates a state of the art rain intrusion model which computes interior damage, as opposed to the heuristic interior damage model still currently implemented in the personal residential model of version 4. The ultimate goal is to have both the personal and the commercial residential models converge into a single model. This research reports the preliminary attempt to do so. Although a complete integration of the commercial and personal residential components of the FPHLM was not achieved, the framework and foundation have been established for what will be version 5 of the FPHLM.
Abstract: The Florida Public Hurricane Loss Model is a catastrophe model commissioned by the State of Florida with the primary purpose of predicting insured losses of residential buildings due to hurricanes. The model has been in a state of ongoing development since 2001, and is contributed to by several universities around the state of Florida.
The model is comprised of three main components. The Meteorological Component predicts and models hurricane behavior. The Vulnerability Component predicts and models building damage given specific wind conditions. Lastly, the Actuarial Component takes data from the other two to predict and analyze specific scenarios. This paper presents several updates to the Vulnerability Component of the model.
First, a more realistic cost analysis is presented, created based on information gathered from actual building contractors as well as RS Means. The new cost analysis includes updates such as unit costs that scale with repair size, considerations for actual roof repair methodology, and various other factors specific to the particular building requirements and market conditions of Florida.
Second, an analysis of Type 2 curves, which allow the Vulnerability Component of the model to be validated independent of the Meteorological Component, is shown. A procedure for their use in model validation is also given, along with a brief sample validation which illustrates the usefulness of the Type 2 curves in uncovering hidden issues with the model.
Finally, a brief study analyzing the effects of the changes made to the wind provisions of ASCE 7 is presented. The study shows that the changes implemented in ASCE 7-10 will have little effect, in the case of low-rise, personal residential buildings, on actual building practices in the state of Florida.
|2014||Gonzalo Pita, Jean-Paul Pinelli, Kurt Gurley, Judith Mitrani-Reiser, “State of the Art of Hurricane Vulnerability Estimation Methods: A Review,” submitted for publication to the ASCE Natural Hazard Review.|
|2014||Boback Bob Torkian, Jean-Paul Pinelli, Kurt Gurley, Shahid Hamid, “Cost and Benefit Evaluation of Windstorm Damage Mitigation Techniques in Florida," ASCE Natural Hazard Review, May 2014, 15:150-157.|
|2013||Gonzalo L. Pita, Jean-Paul Pinelli, Kurt Gurley, Shahid Hamid, “Hurricane Vulnerability Modeling: Evolution and Future Trends,” Journal of Wind Engineering & Industrial Aerodynamics, 114 (2013) 96–105.|
|2012||G. L. Pita, J.-P. Pinelli, S. Cocke, K. Gurley, J. Mitrani-Reiser, J. Weekes, S. Hamid, “Assessment of hurricane-induced internal damage to low-rise buildings in the Florida Public Hurricane Loss Model,” Journal of Wind Engineering & Industrial Aerodynamics, 104-106 (2012), 76-87.|
|2011||Pinelli, J.-P., Pita, G., Gurley, K., Torkian, B., Hamid, S., Subramanian, C., “Damage Characterization: Application to Florida Public Hurricane Loss Model,” ASCE Natural Hazard Review, November 2011, Vol. 12, No. 4, pp. 190-195.|
|2011||Hamid, S., Pinelli, J.-P., Cheng, S.-C., and Gurley, K., “Catastrophe Model Based Assessment of Hurricane Risk and Estimates of Potential Insured Losses for the State of Florida,” ASCE Natural Hazard Review, November 2011, Vol. 12, No. 4, pp. 171-183.|
|2008||Pinelli, J.-P, Gurley, K., Subramanian, C., Hamid, S., and Pita, G. “Validation of a probabilistic model for hurricane insurance loss projections in Florida,” Reliability Engineering and System Safety International Journal, Vol. 93, No 12, pp. 1896-1905, December 2008.|
|2004||Pinelli, J-P., Simiu, E., Gurley, K. , Subramanian, C., Zhang, L., Cope, A., Filliben, J., and Hamid, S., “Hurricane Damage Prediction Model for Residential Structures”, Journal of Structural Engineering, ASCE, Vol. 130, No 11, pp 1685-1691.|
|2000||Pinelli, J.-P., and O’Neill, S., “Effect of tornadoes on residential masonry structures.” Wind and Structures Journal, Vol. 3, No 1, March 2000.|
|2013||G. Pita, J-.P. Pinelli, “Analytical Modeling of Low-rise Building Vulnerability,” Proceedings, 12th Americas Conference on Wind Engineering, June 16-20, 2013, Seattle, WA.|
|2013||J-.P. Pinelli, T. Johnson, K. Gurley, J. Weekes, G. Pita, S. Cocke, S. Hamid, “Vulnerability Model for Mid/High-Rise Buildings Subjected to Hurricane Winds and Rain,” Proceedings, 12th Americas Conference on Wind Engineering, June 16-20, 2013, Seattle, WA.|
J.-P. Pinelli, K. Gurley, G.L. Pita, T. Johnson, J. Weekes, “Modeling the vulnerability of mid/high rise commercial residential buildings to wind and rain in tropical cyclones,” Proceedings, 11th International Conference on Structural Safety & Reliability, June 16-20, 2013, Columbia University New York, NY.
|2012||J.-P. Pinelli, T. Johnson, G.L. Pita, K. Gurley, “Life-cycle assessment of personal residential roof decking and cover under hurricane threat,” Proceedings, Advances in Hurricane Engineering, October 24-26, Miami, FL.|
|2012||Gonzalo Pita, Jean-Paul Pinelli, Judith Mitrani-Reiser, Tak Igusa, Kurt Gurley, “Analysis of Hurricane Andrew Insurance Claim Data for Residential Buildings,” Proceedings, Advances in Hurricane Engineering, October 24-26, Miami, FL.|
|2012||G.L. Pita, J.-P. Pinelli, “Probabilistic Hurricane Rain Model for the Evaluation of Building Damage Due to Water Penetration,” Proceedings, ESREL 12, June 25-29, Helsinki, Finland.|
|2011||J.-P. Pinelli, G.L. Pita, “Management of Hurricane Risk in Florida,” Proceedings, ESREL 11, September 18-22, Troyes, France.|
|2011||G.L. Pita, J.-P. Pinelli, “Analytical Method for Low Rise Building Vulnerability Curves,” Proceedings, ESREL 11, September 18-22, Troyes, France.|
|2011||G.L. Pita, J.-P. Pinelli, K. Gurley, J. Weekes, S. Hamid, “Challenges in Developing the Florida Public Hurricane Loss Model for Residential and Commercial-Residential structures,” Proceedings, 11th International Conference on Applications of Statistics and Probability in Civil Engineering, August 1-4, Zurich, Switzerland.|
|2011||G.L. Pita, J.-P. Pinelli, 'Wind Vulnerability Curves Assessment in the Florida Public Hurricane Loss Model,' Proceedings, ICVRAM 2011, Hyattsville, MD, April 11-13, 2011.|
|2011||Boback Bob Torkian, Jean-Paul Pinelli, Kurt Gurley, Shahid Hamid, “Classification of Current Building Stock for Hurricane Risk Analysis,” Proceedings, ICVRAM 2011, Hyattsville, MD, April 11-13, 2011.|
|2011||Jean-Paul Pinelli, Gonzalo Pita, Kurt Gurley, “ Improved Prediction Model for Tropical Cyclone-Induced Damage to Building Interior, Utilities, and Contents,” Proceedings, 5th International Symposium on Wind Effects on Buildings and Urban Environment, Tokyo, March 7-8, 2011.|
|2010||Pita, G., Pinelli, J.-P., Mitrani-Reiser, J., Gurley, K., Weekes, J.,” Latest Improvements in the Florida Public Hurricane Loss Model,” Proceedings, 2nd AAWE Workshop, Marco Island, FL, August 18-19.|
|2010||Boback Bob Torkian, Jean-Paul Pinelli, Kurt Gurley, “Mitigation Techniques to Improve Residential Buildings Behavior During Hurricanes,” ASCE 2010 Structures Congress, May 2010, Orlando, FL.|
|2010||J.-P. Pinelli, G.L. Pita, K. Gurley, C. Subramanian, S.Hamid, “Commercial-Residential Buildings Vulnerability in the Florida Public Hurricane Loss Model,” ASCE 2010 Structures Congress, May 2010, Orlando, FL.|
|2009||G. L. Pita, J.-P. Pinelli, J. Mitrani-Reiser, K.Gurley, S.Hamid, N. Jones, “Risk analysis of Buildings with the Florida Public Hurricane Loss Model.” Society of Risk Analysis. Baltimore, December 2009.|
|2009||Jean-Paul Pinelli , Shahid S. Hamid , Kurt Gurley , Gonzalo Pita, " Florida Public Hurricane Loss Model: Vulnerability Modeling, Loss Prediction, and Certification Process", Proceedings, 2nd International Conference on Asian Catastrophe Insurance, Beijing, China, December 8-9, 2009.|
|2009||Gonzalo Pita, Jean-Paul Pinelli, Kurt Gurley, Chelakara Subramanian, Jonathan Weekes, and Shahid Hamid, “Vulnerability of mid-high rise commercial-residential buildings in the Florida Public Hurricane Loss Model,” Proceedings, ESREL 09, Prague, Czech Republic , September 7-10, 2009.|
|2009||Jean-Paul Pinelli, Boback Torkian, Kurt Gurley, Chelakara Subramanian, and Shahid Hamid, “Cost effectiveness of hurricane mitigation measures for residential buildings” Proceedings, 11th Americas Conference on Wind Engineering, San Juan, Puerto Rico, June 22-25, 2009.|
|2009||Gonzalo Pita, Jean-Paul Pinelli, Kurt Gurley, Chelakara Subramanian, and Shahid Hamid, “Vulnerability of low-rise commercial-residential buildings in the Florida Public Hurricane Loss Model” Proceedings, 11th Americas Conference on Wind Engineering, San Juan, Puerto Rico, June 22-25, 2009.|
|2008||Gonzalo Pita, Jean-Paul Pinelli, Chelakara Subramanian, Kurt Gurley, and Shahid Hamid, “Hurricane Vulnerability of Multi-Story Residential Buildings in Florida,” Proceedings, ESREL 08, Valencia, Spain, September 22-25, 2008.|
|2008||Jean-Paul Pinelli, Shahid Hamid, Kurt Gurley, Gonzalo Pita, and Chelakara Subramanian, “Impact of the 2004 Hurricane Season on the Florida Public Hurricane Loss Model,” Proceedings, ASCE 2008 Structures Congress, April 24-26, 2008, Vancouver, Canada.|
|2007||Jean-Paul Pinelli, Chelakara Subramanian, Kurt Gurley, and Shahid Hamid « Validation of the Florida Public Hurricane Loss Projection Model,” Proceedings, 12th International Conference in Wind Engineering, Cairns, Australia, July 1-6, 2007.|
|2006||Jean-Paul Pinelli, Chelakara Subramanian, Arturo Artiles, Kurt Gurley, and Shahid Hamid, “Validation of a probabilistic model for hurricane insurance loss projections in Florida,” Proceedings, ESREL 06, Estoril, Portugal, September 18-21, 2006.|
|2005||Jean-Paul Pinelli, Chelakara Subramanian, Kurt Gurley, Shahid Hamid, and Sneh Gulati, “Hurricane Loss Prediction Model and Coastal Mitigation,” Proceedings, 4th European and African Conference on Wind Engineering, Prague, July 11-15, 2005.|
|2005||Jean-Paul Pinelli, Chelakara Subramanian, Kurt Gurley, Sneh Gulati, Shahid Hamid, Josh Murphree, and Anne Cope, “Hurricane Loss Prediction: Model Development, Results, and Validation,” Proceedings, ICOSSAR 2005, Rome, Italy, June 19-23, 2005.|
|2005||Jean-Paul Pinelli, Chelakara Subramanian, Kurt Gurley, Shahid Hamid, and Sneh Gulati, “Florida Hurricane Loss Prediction Model: Implementation and Validation” Proceedings, 10th Americas Conference on Wind Engineering, Baton Rouge, Louisiana, May 31- June 4, 2005.|
|2004||Jean-Paul Pinelli, Josh Murphree, Chelakara Subramanian, Kurt Gurley, Anne Cope, Shahid Hamid, and Sneh Gulati, “Hurricane Loss Estimation Model,” Proceedings ESREL 2004, Berlin, Germany, June 2004.|
|2003||Jean-Paul Pinelli, Chelakara. Subramanian, Liang Zhang , Kurtis Gurley, Anne Cope, Emil Simiu, Sofia Diniz, and Shahid Hamid, ,”A Model to Predict Hurricanes Induced Losses for Residential Structures” 35th Joint US-Japan Panel Meeting on Wind & Seismic Effects 12-17 May 2003, Tuskuba, Japan.|
|2003||Pinelli, J-P., Zhang, L., Subramanian, C., Cope, A., Gurley, K., and Gulati, S., “Classification of Structural Models for Wind Damage Predictions in Florida,” Proceedings, 11th International Conference in Wind Engineering, Lubbock, Texas, June 2003.|
|2003||Pinelli, J-P., Subramanian, C., Zhang, L., Gurley, K. , Cope, A., Simiu, E., Filliben, J., and Diniz, S., “A Model to Predict Hurricanes Induced Losses for Residential Structure,” Proceedings, European Safety and Reliability Conference, Maastricht, The Netherlands, June 2003.|