New AHA Tool Helps Predict the Hidden Effects of Disasters
The Idaho National Laboratory (INL) has developed a new disaster prediction tool – the All Hazards Analysis (AHA) software – which is designed to enhance emergency preparedness by helping emergency managers identify the downstream impact of disasters on vulnerable, critical assets.
The software works by mapping the relationships and integrations of various downstream facilities and assets within a given town or community – for example, predicting how a natural gas shortage might force a gas-fired power plant to shut down, or how a disruption in the supply of critical chemicals might prevent a wastewater plant from properly operating.
Impetus for Developing the AHA Software
INL began development of the tool in response to the downstream impact of Hurricane Maria in 2017. It’s well-known that Maria caused widespread destruction across Puerto Rico, but lesser known is how the storm impacted the island’s healthcare supply chain. Specifically, a major supplier of IV bags had its operations interrupted, which resulted in a shortage of these critical items across the local hospital network.
It goes without saying that this “hidden” downstream impact was unanticipated. As with most critical infrastructure, the IV bag supply chain was out of sight and out of mind for the vast majority of emergency managers in Puerto Rico. But that should now change with the launch of AHA.
The first step to develop the AHA model is to deploy an autonomous, machine learning-driven process to gather data about essential infrastructure and supply chains, including those around water, wastewater, electricity, fuels, telecommunications, even hospital supply chains, for blood products and medicines. This data, which includes physical assets as well as informational documentation such as technical references and design standards, is then analyzed and integrated into the software.
Once the data is loaded and analyzed, simulations are run to identify and understand the downstream impact of a disaster on various pieces of infrastructure, processes, assets and facilities. This modeling self-learns and naturally evolves over time to help optimize emergency planning and recovery operations.
The bottom line is that anything that can assist with emergency planning is a plus, and AHA is certainly no exception. Hopefully the software will continue to expand and evolve to the point where it will be a must-have tool in the tool chest for emergency preparedness personnel in the utility industry.
