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Nuclear Accident Probabilities

Scott D. PortzlineThree Mile Island Alert

Harrisburg PASeptember 2013

The U.S. Nuclear Regulatory

Commission still doesn’t get it.

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but Las Vegas gets it

If the Nuclear Regulatory Commission used its faulty accident probabilities to run a Las Vegas style casino, they’d have been bankrupt in the first year.

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Probabilities & Timingsimply stated:

The NRC’s probabilities are an analysis of an event’s likelihood of occurring over a period of time.

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Las Vegas can bank on it’s accuracy because there is far more certainty in the mathematics of systems that do not involve breakdowns, human errors, electrical failures, mis-management etc..

Of course the NRC has been unable to calculate those factors with accuracy.

Probabilities & Timing

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but Government’s buy into itGovernments need to know what risks are associated with nuclear power. Therefore, the nuclear industry creates favorable probabilistic risk analyses in order to get the governmental “green light.”

Risks vs. Rewards

Here is an example…. a

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The NRC’s first probabilistic risk study, the Rasmussen Report, was used to persuade Congress to extend the insurance policy for the nuclear power industry.

Government’s buy into it

The Probability of an Accident

The Rasmussen Report gave the odds as

1 chance in 1 million per reactor per year

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A Clever PhraseA mathematician will use a probability risk study to say something like ….

“You are more likely to be struck by a meteor than to have a nuclear accident.”

(We were told this at Three Mile Island.)

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But it’s just a Clever Phrase

We’re still waiting for the meteor!

March 28, 1979

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Ironic Timing

Just two months prior to the TMI accident the NRC was forced to disavow its accreditation of the Rasmussen Report.

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and ConfusingHowever, the NRC could not say if the odds of an accident were greater or less than Rasmussen had predicted.

This amounted to an admission that it did not understand its own study or which side of the fence to fall on.

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Data vs ConclusionsThe biggest problem was that the technical data did not support the conclusions touted in the executive summary.

This caused one NRC Commissioner to state that he thought the Rasmussen report was used for propaganda to persuade Congress.

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More ConfusionThen another analysis after TMI concluded:

“…about 20 factors contributed to the damaging results at Three Mile Island. If any one of these factors had been different -- in a way which is common in other plants -- there would have been no core damage and no release of radioactivity.”

Electric Power Research InstituteMarch 1980

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Longer than a Long-ShotIn other words, all 20 factors came up against all odds.

Vegas would never let that happen.

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Longer than a Long-ShotWith long-shots like that, Vegas would be “broke” many times over.

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After the TMI accident, still another analysis showed that the odds as presented in the Rasmussen Report were accurately predictive of the occurrence of the TMI accident. Only, now the odds were described as 1 chance in 7.7 of an accident occurring.

Even More Confusion

Odds: 1 chance in 7.7 of an accident at the time of TMI

Report of the Technical Assessment Task Force Vol. 1Kemeny Commission

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Interpretation of Rasmussen Report before TMI

Even More Confusion

Odds: 1 chance in 1 million per reactor per year.

Odds: 1 chance in 7.7 of an accident vs. afterwards

Government’s don’t like these odds

What government would green light a project with a 13% risk of having a severe nuclear accident?

1 chance in 7.7 = 13%

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Interpretations vary widely

As you can see, interpretations of the probabilities for the same incident are “all over the map.”

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An aptitude test was given to three applicants at a public relations firm.

Question: What does 1/3 mean to you?

The purest answered, .33333The theorist answered, “one third”The statistician answered, “What do you want it to say?”

WANTED: MATHEMATICIAN

Anecdote

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Subject to ManipulationPRAs do yield numerical estimates and are thus “quantitative.” Some scientists believe the estimates are so imprecise and subject to manipulation as to be virtually useless in decision making.

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Human Factors Reliability Benchmark Exercise,Commission of the European Communities, 1989

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Probabilities & Humans

Estimates for the occurrence of “human error” have varied by a factor of ten thousand.

Varied by

a Factor of

10,000!

Human Factors Reliability Benchmark Exercise,Commission of the European Communities, 1989

That means that older NRC accident PRAs could be off by 4 orders of magnitude on the human aspects alone.

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Probabilities & Humans

The more recent international HRA empirical study in 2011, sponsored by the NRC has found that, twenty years later, large variability appears to remain.

Science-Based Simulation Model Of Human Performance forHuman Reliability AnalysisIdaho National Laboratory

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The human contribution to the risk of operation of complex technological systems is significant, with typical estimates lying in the range of 60-85%.

Probabilities & Humans

Case Study Report on Loss of Safety System Function Events, AEOD/C504,Washington, DC: U.S. Nuclear Regulatory Commission, 1985

Therefore PRA’s cannot be accurately modeled, since human behavior varies greatly, even for the same event.

4 common flaws of NRC Probabilistic Risk Analyses (PRAs)

The conclusion(s) are not always supported by the data.

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4 common flaws of NRC PRAs

Some data has been cherry-picked while other data is ignored.

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The data is applied to faulty Modeling

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4 common flaws of NRC PRAs

Incomplete processing

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4 common flaws of NRC PRAs

All four of these deficits are found in the NRC’s latest severe accident study called SOARCA. They are described in detail with examples in my report.

http://www.efmr.org/files/2012/SOARCA-2-22-2012.pdf

SOARCA is another example of a probability study gone awry.

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4 common flaws of NRC PRAs

Extraordinary flaw of NRC PRAsThe NRC provides false conclusions to Congress.

The NRC Commissioners testified that a Fukushima-type accident can not happen in the US. Flooding by tsunami triggered the accidents.

However, one of their own PRAs shows that there is a 100% chance of a meltdown at a specific US plant (unnamed here for security reasons) if a nearby upstream dam were to fail.

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Conclusion #1The confidence of the nuclear industry is falsely bolstered by exaggerated probabilities.

Furthermore, these unwarranted confidences morph into an attitude that an accident is possible, but it won’t happen “here” or “any time soon.”

Mantra: “defense in depth.”

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Conclusion #2These attitudes created conditions that led to Three Mile Island and Fukushima.

Specifically: At TMI, the industry banked on numerous backup systems which were not available, did not work properly, or were disabled prior to and during the accident. “Defense in depth” did not succeed. (see slide #13)

At Fukushima, the industry and the government banked on the probabilities of Tsunami height. The entire chain after that point was defeated.

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Conclusion #3There is a long chain of safety systems with many variables. Too many to accurately quantify in a probabilistic risk analysis.

The NRC is able to understand and quantify certain (but not all) shorter segments of the chain.

However the NRC cannot quantify the risks for the entire chain.

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Conclusion #4Insurance companies and Las Vegas are very good at probabilities. Neither one is in the nuclear game for good reason.

The NRC should not place a heavy reliance upon PRAs in their licensing and safety analyses and processes.

The NRC should likewise not use PRAs in testimony to governmental bodies until the time comes when they have a far better track record.

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