Made Suarjana

Comparison of preconditioned conjugate gradient method and LDLT factorization for structural analysis

This paper compares the efficiency of the preconditioned conjugate gradient (PCG) method and the LDL T factorization for solving a sparse system of linear equations in large-scale structural analysis with both single- and multiple-load cases. In the PCG method we present an incomplete LDL T preconditioning method that can be used to efficiently solve a system of linear equations with a wide range of matrix conditions, system sizes, and computer memory limitations. The preconditioning method is very flexible, and we can easily balance the size of the preconditioning matrix and the level of the preconditioning that is appropriate for the problem to be solved. For comparison, we use an implementation of a row-oriented sparse LDL T solution method.

Empirical fatality model for Indonesia based on a Bayesian approach

Abstract An empirical fatality model for Indonesia has been developed by relating the macroseismic intensity to the fatality rate using compiled sub-district level fatality rate data and the numerically simulated ground-shaking intensity for four recent damaging events. The fatality rate data were compiled by collecting population and fatality statistics of the regions affected by the selected events. The ground-shaking intensity was numerically estimated by incorporating a finite-fault model of each event and local site conditions approximated by topographically based site amplifications. The macroseismic intensity distribution of each event was generated using ShakeMap software, combining a selected pair of ground motion prediction equations and ground motion to intensity conversion equations. The developed fatality model is a Bayesian generalized linear model in which the fatality rate is assumed to follow a mixture of Bernoulli and gamma distributions. The model was validated by calculating the fatalities in past events from the EXPO-CAT catalogue and comparing the estimates with the EXPO-CAT fatality records. Although the model can provide an estimate of the range of fatalities for future events, it needs ongoing refinement by the incorporation of additional fatality rate data from past and future events.