“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 can we identify internal vulnerabilities in infrastructure?”
In the physical world, imperfections can be found in every little structure. This also holds true for infrastructure. Resilience Vulnerabilities are the parts of infrastructure that may be liable in case a situation happens. Examples include not having backup generators or having structurally weak cement for the building.
“How can we quantify external threats against resilience?”
Unexpected events such as natural disasters and power outages can cause unexpected damage to infrastructure. In resilience analysis, these are often quantified as Resilience Threats. Example resilience threats include sea-level rise against coastal installations and natural gas pipeline bursts.
How Risk Analysis Can Be Used to Determine an Area’s Proneness to Wildfires
“How can we use risk analysis techniques to assess an area’s proneness to wildfires?”
With the ascent of climate change, the natural environment is becoming more unstable. In dry areas with sufficient vegetation, this means that wildfires are becoming more common. As such, people will need to understand what areas of liable to become aflame. This can be accomplished using risk analysis techniques which take into account the dryness, lack of rainfall, and temperatures of a particular area to produce a risk assessment. This is How Risk Analysis Can Be Used to Determine an Area’s Proneness to Wildfires.
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How Probability Distributions Can Help with Risk Assessment
“How can we use probability distributions to create risk assessments?”
One of the most important parts of any engineering project is to analyze the risks involved in any process. However, quantifying these issues can prove to be quite difficult. To solve this, statisticians and engineers have worked together to create methods based upon preexisting probability distributions to help with the risk assessments. For example, an exponential decay distribution can be used to model a reliability function or a binomial distribution can be used to analyze failure of a specific component. This is How Probability Distributions Can Help with Risk Assessments.
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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.
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“How can we assess risk?”
If phenomenon has a possibility of occurring with malignant effects it is classified as a risk. The origin of the risk, its spread, and its malignant effects can all be assessed. However, these all can be brought together under a complete Risk Assessment, which gives a holistic and quantitative overview of the entire picture.
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