Property Damage vs Release Volume

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 […]

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 […]

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 […]

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 […]

It sounds like you have methods that very accurately predict failure potential. Is this true?

Unfortunately, no. While the new modelling approaches are powerful and the best we’ve ever had, there is still huge uncertainty. We are unable to accurately predict failures on specific pipe segments except in extreme cases. With good underlying data, we can do a decent job of predicting the behaviour of numerous pipe segments over longer […]