“How can we simulate wildfires?”
Wildfires can cause damage in often unpredictable ways. In order to add a deeper level of risk analysis to this, Wildfires Simulations can be done to compute what a possible wildfire would look like. Wildfire simulations can take in aspects such as Wind speed, wind direction, fuel moisture content, fuelscape, ignition location, ignition probability, containment probability, fire duration.
Image credit http://www.firelab.org
“How is it that some losses are to be expected?”
Although we try to make ourselves as resilient as possible to disasters, sometimes losses are bound to occur. For this reason, Expected Losses can be calculated and projected as risk and calculated using statistical methods.
How Climate Change Is Making the Bay Area Windier and More Prone to Fires
“Why is a windier Bay Area more at risk of fires?”
The Earth’s climate is changing more and more as larger volumes of carbon dioxide are poured into the atmosphere. Nothing seems to be unaffected, not even wind speeds. Although the data right now is scarce, current projections are showing that Northern California is experiencing windier seasons years after year in the autumn, which when combined with dry and hot conditions can lead to wildfires. As a result, government officials may need to think about how to incorporate this issue into their resilience planning. This is How Climate Change Is Making the Bay Area Windier and More Prone to Fires.
Image credit https://climatefeedback.org/
“How can we make our infrastructure more resilient against hurricanes?”
With the advent of climate change, hurricanes are becoming more and more powerful. Just by witnessing the devastating aftermath from storms such as Katrina and Marina one can see that infrastructure in storm-prone areas needs to be redeveloped around Hurricane Resilience. Hurricane resilience can take many forms, such as hardening structures against wind to making streets more permeable to an influx of water.
Discrete Reliability Function
“How can we have a reliability function in a discrete form?”
Reliability functions are useful for predicting how long a component will last for. However, sometimes real-world data will not give a continuous output. This can be solved by using a Discrete Reliability Function which is more flexible to such needs.
Image credit upload.wikimedia.org
“How can we assess the consequences of a risk?”
Risks are something that come in every engineering system, whether it be the probability that a dam overflows or a forest fire breaks out. However, how can we assess what will be the effects of the mishap on the surrounding community? Well, we can perform a Consequence Assessment to quantify or categorize how harmful things will be.
“How can we analyze the probability of a risk factor breaking out?”
Risk is one of the most important components in infrastructure projects, whether it be related to the structural integrity of a bridge or the temperature levels of a nuclear power plant. If something goes wrong, it could end up costing billions of dollars. So how can we analyze and quantify the release of such events. Well, we can perform something called a Release Assessment, which integrates every possible factor that could lead to failure.
“How can we model how long something is expected to survive?”
One of the most fundamental laws of physics is that the total amount of entropy can only increase. Consequently, everything in the physical domain will wear out over time and eventually no longer function. Since the survival of many projects and people are responsibilities of many engineers and medical practitioners, these professions are interested in how long things are expected to last. This can be accomplished using a Reliability Function, (also known as a survival function in medicine), which models the statistical lifetime of an object of interest as a cumulative distribution function. These can play out in any number of ways, but the starting point must always be equal to 100% and the endpoint zero.
Image credit upload.wikimedia.org