Building on existing MATLAB applications, the GA team wrote the vulnerability code and used MATLAB to simulate local ground shaking, calculate building damage, and predict the effect of the simulated earthquake on surrounding rock and soil. “Having the ability to streamline tasks within one integrated environment was very beneficial,” Robinson says. They used historical and geological information about previous earthquakes to constrain the probability of future earthquakes in terms of magnitude and location.
“MATLAB lets us handle large data sets and perform calculations efficiently and quickly,” says Robinson. “Using the built-in MATLAB functions, it was easy to sort and find the required data from within very large matrices. The new JIT-Accelerator and some clever programming in MATLAB enabled us to perform routines more than six times faster.”
For earthquake hazard models, the team used MATLAB routines to sort through the matrices to identify events of interest and estimate the hazard. To estimate the building damage, they used functions in MATLAB to efficiently calculate the maximum building displacement and acceleration for each of the 6,000 buildings in the database. They used this data to calculate the probabilities of being in a given damage state. They then calculated the economic damage for each building by aggregating the dollar loss for all buildings in Newcastle for a specified period.
Geoscience Australia now has models that define the probability of a future earthquake, define the levels of ground shaking in relation to the distance from the earthquake, and its expected impacts. Based on this data, they have made recommendations to the Earthquake Loading Standards Committee of Australia, which is responsible for developing building codes that will help protect new buildings and key facilities, such as emergency services and hospitals, from earthquake damage.