Guillermo Franco

Probabilistic Benefit-Cost Analysis for Earthquake Damage Mitigation: Evaluating Measures for Apartment Houses in Turkey

In the wake of the 1999 earthquake destruction in Turkey, the urgent need has arisen to evaluate the benefits of loss mitigation measures that could be undertaken to strengthen the existing housing stock. In this study, a benefit-cost analysis methodology is introduced for the comparative evaluation of several seismic retrofitting measures applied to a representative apartment building located in Istanbul. The analysis is performed probabilistically through the development of fragility curves of the structure in its different retrofitted configurations. By incorporating the probabilistic seismic hazard for the region, expected direct losses can be estimated for arbitrary time horizons. By establishing realistic cost estimates of the retrofitting schemes and costs of direct losses, one can then estimate the net present value of the various retrofitting measures. The analysis in this work implies that, even when considering only direct losses, all of the retrofitting measures considered are desirable for all but the very shortest time horizons. This conclusion is valid for a wide range of estimates regarding costs of mitigation, discount rates, number of fatalities, and cost of human life. The general methodology developed here for a single building can be extended to an entire region by incorporating additional structural types, soil types, retrofitting measures, more precise space- and time-dependent seismic hazard estimates, etc. It is hoped that this work can serve as a benchmark for more realistic and systematic benefit-cost analyses for earthquake damage mitigation.

On the Uniqueness of Solutions for the Identification of Linear Structural Systems

This work tackles the problem of global identifiability of an undamped, shear-type, N degrees of freedom linear structural system under forced excitation without any prior knowledge of its mass or stiffness distributions. Three actuator/sensor schemes are presented, which guarantee the existence of only one solution for the mass and stiffness identification problem while requiring a minimum amount of instrumentation (only I actuator and 1 or 2 sensors). Through a counterexample for a 3DOF system it is also shown that fewer measurements than those suggested result invariably in non-unique solutions.

Post-December 2004 Tsunami Reconstruction in Sri Lanka and Its Potential Impacts on Future Vulnerability

The 26 December 2004 tsunami displaced more than 500,000 people and killed an estimated 31,000 in Sri Lanka. Damage was not uniform, often reflecting distinct patterns of social, infrastructural, and ecological vulnerability. Severely affected populations tended to be poorer, to live in fragile structures, and to be more exposed to the tsunami as a result of prior environmental degradation in the coastal zone. The massive reconstruction effort may further decrease the resilience of rural communities by degrading the natural environment that sustains their livelihoods. A sustainable reconstruction approach must therefore consider long-term solutions that increase community resilience by fostering socioeconomic, infrastructural, and environmental progress. A reconnaissance team monitored the initial recovery stages and identified mechanisms in supporting research on reducing the long-term vulnerability of human settlements and ecosystems to future environmental hazards.

Rebuild Fast but Rebuild Better: Chile's Initial Recovery Following the 27 February 2010 Earthquake and Tsunami

The Chilean earthquake and tsunami disaster of 27 February 2010 impacted 12 million people in 900 cities and towns, causing more than US

Minimization of Trigger Error in Cat-in-a-Box Parametric Earthquake Catastrophe Bonds with an Application to Costa Rica

30 billion in losses. This paper considers how the national government responded to the challenges of coastal and urban reconstruction, and examines the actions taken in the housing, land use mitigation planning, insurance, and risk reduction management sectors. The Chilean government utilized a mixed decentralized model for recovery management with strong direction from the national-level ministries and subnational planning and housing efforts at the regional and municipal levels. The national recovery plan guiding principles are used in this paper as a framework for progress. In 12 months, a series of temporary shelter villages and a system of recovery housing subsidies were established; risk-based land use plans were conducted in various coastal areas; a finance plan was adopted; changes to the national emergency management agency were made; and rapid payment of insurance claims were completed. Conflicts did arise related to the speed of housing recovery support, expropriation of land sites as future tsunami protection barriers, and extent of public participation in recovery plan making.

Minimizing Trigger Error in Parametric Earthquake Catastrophe Bonds via Statistical Approaches

Catastrophe bonds are used by the insurance and reinsurance industry and by national governments to cede catastrophic risks to the financial markets. Triggers whose outcomes depend only on the earthquake parameter data published by respected third parties can be implemented to determine without moral hazard whether the bond principal is paid for a certain event. Sensitivity analyses to different design assumptions show that these transactions are often affected by trigger error, unless a sufficiently dense geographic discretization is selected to define the trigger zones. A process of general application to any geography is developed to minimize the trigger error. The methodology is illustrated with the design of a hypothetical cat bond for Costa Rica.

Identification of structural damage using dynamic input-output measurements

The insurance and reinsurance industry, some governments, and private entities employ catastrophe (CAT) bonds to obtain coverage for large losses induced by earthquakes. These financial instruments are designed to transfer catastrophic risks to the capital markets. When an event occurs, a Post-Event Loss Calculation (PELC) process is initiated to determine the losses to the bond and the subsequent recoveries for the bond sponsor. Given certain event parameters such as magnitude of the earthquake and the location of its epicenter, the CAT bond may pay a fixed amount or not pay at all. This paper reviews two statistical techniques for classification of events in order to identify which should trigger bond payments based on a large sample of simulated earthquakes. These statistical techniques are effective, simple to interpret and to implement. A numerical experiment is performed to illustrate their use, and to facilitate a comparison with a previously published evolutionary computation algorithm.

Statistical and machine learning approaches for the minimization of trigger errors in parametric earthquake catastrophe bonds

This paper presents a variety of methodologies that are used to detect the location and amount of structural damage using dynamic measurements of the input and of the structural response. One approach (and its variations) starts from an identified first order model of a structural system and obtain estimation of the structures mass, damping and stiffness matrices. For these approaches, both the full instrumentation option and the partial instrumentation option are presented. An alternative approach for the identification of the dynamic characteristics of the structure is based on Evolution Strategies. Once these dynamic characteristics have been determined, structural damage is assessed by comparing the undamaged and damaged estimation of such parameters. Both these methodologies are tested on simulated numerical results and their effectiveness in determining structural damage is evaluated.

Uniqueness of Solutions for the Identification of Linear Reduced Order Structural Systems

Catastrophe bonds are financial instruments designed to transfer risk of monetary losses arising from earthquakes, hurricanes, or floods to the capital markets. The insurance and reinsurance industry, governments, and private entities employ them frequently to obtain coverage. Parametric catastrophe bonds base their payments on physical features. For instance, given parameters such as magnitude of the earthquake and the location of its epicentre, the bond may pay a fixed amount or not pay at all. This paper reviews statistical and machine learning techniques for designing trigger mechanisms and includes a computational experiment. Several lines of future research are discussed.

Post-disaster recovery dilemmas: challenges in balancing short-term and long-term needs for vulnerability reduction

The problem of identification of structural systems is an inverse problem that uses input (say force excitation) and output information (accelerations, for instance) to obtain an optimal model to describe the system’s behavior. Since a full instrumentation setup is expensive, situations usually arise where only partial measurements are available. Uniqueness of the solution in these circumstances might not be guaranteed. This paper analyzes the minimum number of measurements required to ensure that only one solution exists for the identification problem of mass, damping and stiffness distributions of shear-type N degrees of freedom linear structures. Three typical configurations of measurements are studied with two distinct theoretical approaches, one based on classical polynomial theory, the other based on reduced order model theory. Both these approaches lead to the conclusion that only one input and one or two output measurements are sufficient to guarantee uniqueness of identification, depending on the selected location of the input measurement. Additionally, the identification of a 3DOF system is carried out analytically with the usage of Sylvester’s Dyalitic Elimination to show that fewer measurements than the ones proposed lead to non-unique identification. This fact is also illustrated with the usage of a recently developed optimization technique, with which convergence to the different solutions is observed depending on the initial estimate used.Copyright