While we should view database-input information suspiciously, insights may nonetheless emerge. Joel Anderson recently compared the reported property damage costs with the reported release volumes in PHMSA data 2010 to 2018. spill vol vs prop damage cost This is just pipeline spills, excluding tanks, etc. Note this plot is log-log scale so small changes can equate […]
Results for Statistics
Analyzing Risk Estimates
As the practice of pipeline risk assessment continues to advance, we can also focus on the next steps: how do I make sense out of large sets of numbers? what is this risk assessment telling me? Here’s a recent article with some advice: PIN Article: Analyzing Risk Estimates
Statistical Life Valuation
As monetization of risk becomes more mainstream, values must be assigned to the potential for human injury or fatality. The risk assessor need not generate values himself since such numbers are published in various sources. This includes values that have been used in US government decision-making for years. Here is some example guidance: VSL Guidance 2013 […]
Risk Profiling
Pipeline Risk Assessment—Risk Profiling In earlier installments of this column, we introduced the concept of pipeline risk assessment Essential Elements (EE’s). That guideline is a list of ingredients that must be included in any pipeline risk assessment before that assessment can be considered complete. Following these guidelines helps to ensure a technically sound risk assessment […]
CoF Data Analyses
How well do the PHMSA reportable incident consequences track other incident data? More interesting work by Joel Anderson. CoF_multiplot
Decision Trees and Risk Assessment
An interesting contribution from Joel Anderson Pipeline Risk algorithms can take in hundreds of variables and perform hundreds more calculations to determine the probability of failure for a given segment of pipe. Trying to determine what threats are biggest contributor to a system’s risk or even over the length of a given line can be […]
Getting in the Ballpark
There exists a type of risk analysis that is even more preliminary than a rudimentary assessment. This might be termed more of a risk conceptualization rather than assessment and is based solely on basic deductive reasoning. Illustrated by an example, an analyst may posit that a pipeline’s future risks will mirror the losses shown by […]
Is this the same as SRA, LSD?
This recommended pipeline risk assessment methodology is similar to SRA (Structural Reliability Analyses) and LSD (Limit State Design) or LRFD (Load and Resistance Factor Design). This is coincidental, since the methodology was developed independently from these techniques. However, despite the similarities, there are key differences. Similarities include: Focus on engineering principles rather than incident history Accommodates […]
Myth Busting—I don’t have enough data (Part 2)
In the first part of this discussion, we hopefully dispelled some myths about low data availability. We discussed how reasoning is used to generate data and how many useful pieces of risk insight emerge from even simple pieces of knowledge. We also contrasted a statistical approach to risk assessment with a physics based approach. The […]
Pipeline Risk Assessment—Myth Busting Part 1
In the first installment of this column, we introduced the concept of pipeline risk assessment Essential Elements. This is a list of ingredients that arguably must be included in any pipeline risk assessment. In this installment, let’s examine “I can’t do good RA because I don’t have enough data.” There are at least two aspects […]