Video Transcripts

5.3 Risk Analysis Techniques

RENO 9 Quick Start Guide Chapter 9: Risk Analysis ‐ Event Tree for Risk of Fire Damage

Reno quick start guide chapter 9 risk analysis event tree for risk of fire damage

Event trees are analyzes that help you to examine the possible outcomes of a series of subsequent events and trace the pivotal events that lead to a specific end result.

In this chapter, you will explore two ways to create event trees in Reno. The first method uses fixed probabilities; the second method uses simulation.

Event Tree Example

You are evaluating a building’s fire suppression system. The system relies on two subsystems: a sprinkler system and an automatic notification system. If the sprinkler system is not engaged and the fire station is not called, the building is likely to be destroyed. If one of the subsystems fails to react but the other subsystem succeeds, the building is likely to be partially damaged. Your research indicates that there is a 10% chance of fire, a 60% chance of the alert system calling the fire station, and a 70% chance of the sprinklers working.

Objectives:

• use a discrete event tree analysis approach to estimate the probabilities for three different outcomes: the probability that the building will have no damage, the probability that the building will be partially damaged, and the probability that the building will be destroyed.
• Use a simulation approach to solve for the same three outcomes and compare the results.

Note: instead of creating your own project you can open the seven risk analysis event tree risk for fire damage project in the quick start repository to see the Reno flowchart that is created in this chapter.

Discrete Event Tree Analysis

Define the resources

The first step is to define the variables for the given probabilities. Open the resource manager by choosing project, synthesis, resource manager. You click variables in the navigation panel and then choose home, edit, new. Name the variable ProbFire and specify an initial value of 0.1, select the Reset After Analysis option. Follow similar steps to create the ProbCallFireStation variable with initial value equal to 0.6 and the ProbSprinklerWorks variable with initial value equal to 0.7.

Build the flow chart

The next step is to create a flowchart model of the problem. Here is an overview of how the final flowchart will work: fixed probability and the sample project. The flow chart uses binary nodes to branch the analysis into different paths. Each path shows the pivotal events that lead to a specific end result. To create this flowchart model, you first use a standard block to represent the starting point for each simulation. Name the block Start and then enter value 1 in the equation field. This value represents the 100% probability that there will be an outcome to the situation and will serve as the incoming value for the first binary node that follows.

Create a binary node to calculate the probability of fire. Enter the ProbFire variable into the “condition is true” T Path field as shown. The binary node will have two outputs: true and false. The output for the true path will be the incoming value, 1, multiplied by the value of the ProbFire variable, 0.10. The output for the false path will be the incoming value, 1, multiplied by the complement value of the ProbFire variable, 0.9. In other words, the block’s true path will pass the probability that a fire will occur, and the false path will pass the probability that a fire will not occur.

You create another binary node to calculate a pass of probabilities that the sprinkler will work, true path, or won’t work false path.  This time, you enter the ProbSprinklerWorks variable into the “condition is true” T Path field.

Add another binary node to calculate a pass of probabilities that the alarm system will work, true path, or won’t work false path. In this block, you enter the ProbCallFireStation variable into the “condition is true” T Path field. To create a second instance of this same node to be connected to the false path from the Sprinkler Worked node simply copy and paste the block into the correct location.

Next create five result storage blocks to average the results from the five paths in the flowchart. The properties for all five blocks are identical except for the block name, as an example this shows the properties for the No Fire outcome.

The next step is to connect the blocks. You enter the connect blocks mode by choosing flowchart, settings, connect blocks. You then connect the blocks as shown for the true and false paths from each binary node. You make sure to draw the true path first to ensure that the path is properly identified in the flowchart. A true path is green with a “T” above the line, while a false path is red with an “F” above the line. Tip: if you accidentally connect the blocks in the wrong order, you can either delete both lines and start over or change the designations by right-clicking the connector and choosing set to failure or set to success on the shortcut menu.

Simulate the flow chart

Finally, click the simulate icon on the control panel to open the Reno simulation window. Enter one for the number of simulations and specify to use a seed of one for repeatability. You need only one simulation because the binary nodes will model all five sequences of events with a single pass through the flowchart. Click simulate to start the simulation. When simulation is complete, you close the window to return to the flowchart. The values of the results storage blocks are displayed in the flowchart. The results show that there is a 90% chance of a fire not occurring.  There is a 4.2% chance that the sprinklers and alarm will successfully work. This results in a 94.2% chance that the building will have no damage. There is a 2.8% chance that the sprinkler will work, but the alarm system will not. There is also a 1.8% chance that the sprinkler will not work, but the alarm system will. This results in a 4.6% chance that the building will be partially damaged. There is a 1.2% chance that the building will be destroyed because both the sprinkler and alarm failed.

Event tree analysis using simulation

The next step is to solve for the same three outcomes with the simulation approach that uses conditional blocks instead of binary nodes. Typically, simulation is recommended for cases where you don’t have the exact probability data, only models. With this approach, each path through the flowchart results in only 1 of the 5 possible sequences of events, and the results are compiled from the outcomes of a large number of simulations to estimate the probability that each event will occur.

Define the resources

First, open up the resource manager by choosing project, synthesis, resource manager. Select Reno Functions in the navigation panel, then create a new Reno function that will convert the probability values stored in the ProbFire variable into a percentage, that is 10% instead of 0.1. You follow similar steps to create the ProbCallFireStation percent function and the ProbSprinklerWorks present function.

Build the flowchart

You will use the same structure you used in the previous flow chart, but this time, you will use conditional blocks instead of binary notes. To save time, begin by duplicating the original flowchart Fixed Probability in the sample project. You do this by right-clicking the folio in the current project explorer and choosing duplicate on the shortcut menu. Once the duplicate folio is created, rename it to distinguish it from the original flowchart simulation in the sample project.

Next, delete the first binary node called Fire, replace it with the new conditional block.  The new block has the properties shown. Here, the FP is less than or equal to percent condition configures the conditional block to ignore any incoming values; instead, the block will draw a random number uniformly distributed from 0 to 100 and then evaluate whether that number is less than or equal to the condition value. That is whether the random number is less than or equal to 10%. Unlike the binary node, this conditional block is configured to have only one output, true or false. If the condition is true, then a fire occurred, and the simulation sends a value of one to the true path. If the condition is false, then the fire did not occur, and the simulation sends a value of one to the false path. You follow similar steps to replace the remaining binary nodes with new conditional blocks.

For the results storage blocks, you can figure them to calculate the sum of results instead of the average, as shown here for the no-fire outcome. After you’ve restored all the conditions to and from the new conditional blocks, the completed flow chart looks like this.

Simulate the flow chart

You open the Reno simulation window and run 1,000 simulations with a seed of 1 for repeatability.  When the simulation is complete, you close the window to return to the flow chart.

The results show that 942 of the 1000 simulations, 94.2%, result in no fire damage. Forty-three of the 1000 simulations, 4.3%, result in partial damage. In 15 of the 1,000 simulations, 1.5%, the building is destroyed. The results show that both methods yield similar results but with some minor differences due to the random numbers generated by the conditional blocks. Increasing the number of simulations will result in a solution that equals the analytical solution you obtained using the binary nodes.

This concludes Reno quick start guide chapter 9, thank you for watching.

10.4 Frameworks for Sustainable Risk Management

2020 TCFD Status Report – Message from Mike Bloomberg

Hello, I’m Mike Bloomberg, chairman of the Task Force on Climate-related Financial Disclosures. As you know, the COVID-19 pandemic has upended the global financial system, but another crisis has also shocked the system this year: climate change. Wildfires, heat, flooding, and other extreme weather events have devastated communities and cost trillions of dollars this year alone, and all are being fueled by the climate crisis.

At the TCFD, we’ve created standards for businesses to disclose critical information about the impact of climate change to the lenders, insurers, investors, and other stakeholders. The good news is that more than 1,500 organizations in the public and private sectors have now endorsed our recommendations, and this year’s status report shows that more and more companies are adopting them. Government leaders, supervisors, and regulators have also announced policies, partnerships, or support for climate-related disclosures and leaders at every level are making sustainability and resilience a key part of their economic recovery plans.

We still have a long way to go. Investors, asset managers, corporations, governments, and financial institutions have an important role to play and I hope this year’s report helps as we work together to improve climate risk disclosures and make more progress.