2003 ngwa midsouth focus conference september 2003 neptune and company, inc. modeling uncertainty:...

September 20032003 NGWA Midsouth Focus Conference

Neptune and Company, Inc.

Modeling Uncertainty: Modeling Uncertainty: Realism Realism vsvs Conservatism in Conservatism in

Radiological Performance AssessmentRadiological Performance Assessment

John Tauxe, PhD, PEPaul K. Black, PhD

Bruce M. Crowe, PhD

Donald W. Lee, PhD, PE

http://www.neptuneandco.com/~jtauxe/ngwa03


Presentation OutlinePresentation Outline

• What is Performance Assessment?

• Probabilistic PA modeling

• A Low-Level Radioactive Waste example

• Advantages of probabilistic modeling

• Modeling and uncertainty


Quote of the DayQuote of the Day“Reports that say that something hasn't happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns – the ones we don't know we don't know.”

Secretary of Defense Donald H. Rumsfeld DoD News Briefing – 12 Feb 2002

Source: http://www.defenselink.mil/news/Feb2002/t02122002_t212sdv2.html


Performance AssessmentPerformance Assessment• For the DOE and its LLW sites, PAs are

intended to establish “reasonable expectation” that performance objectives are not exceeded (e.g. DOE M 435.1), in order to authorize waste disposal.

• PAs are traditionally deterministic and conservative, yet any such analysis has inherent uncertainties in assumptions, parameter values, and in the models themselves.

435.1

PA

DAS


Determinisitic Determinisitic vsvs Probabilistic Probabilisticpro con

deterministic analysis

• May be appropriate for simple compliance demonstration

• Easy for decision makers and public

• Uncertainties are unspecified

• What is conservative may not be known

probabilistic analysis

• Better represents state of knowledge

• Makes for better informed decisions

• Requires development of input distributions


PAs and UncertaintyPAs and UncertaintySources of uncertainty in PA modeling include

• conceptual model assumptions and exposure scenarios,

• analytical and numerical models and their assumptions, and

• model input parameters in space and time (variability and knowledge uncertainty).

?

?

?

?

??

??

??


Deterministic ModelingDeterministic ModelingDeterministic models

• produce deterministic (single-valued) output with no uncertainty,

• are easy to compare to deterministic performance objectives,

• typically strive for conservatism*, and

• may be a good choice for simple demonstration of compliance.

* What is conservative may not always be obvious, and conservatism can obscure model complexities.


Probabilistic ModelingProbabilistic Modeling

Probabilistic models

• strive to be realistic (not conservative),

• represent uncertainty using probability density functions for model parameters,

• propagate uncertainty through Monte Carlo simulation, and

• calculate model outputs as probability density functions.


An Example from the Nevada Test SiteAn Example from the Nevada Test Site

Area 5 Radioactive Waste Management Site • Photo courtesy NNSA/NSO


The Area 5 RWMSThe Area 5 RWMSThe conceptual model of transport at the Area 5

Radioactive Waste Management Site at the Nevada Test Site includes:

• upward flux of water driven by high evapotranspiration potentials,

• diffusion in liquid and gaseous phases,

• biotic transport of contamination and materials in the near surface, and

• resuspension by wind.

Processes are nonlinear and tightly coupled, so what makes for a conservative estimate?


ground surface

to groundwater

unsaturatedzone flow

divide

no-fluxboundary

Advective/Diffusive TransportAdvective/Diffusive Transport

What is conservative?

Modeled processes:

1. advection of water • down to distant water table • up to “no-flux boundary”

adve

ctio

n in

wat

er

diffu

sion

in w

ater

2. diffusion in water below “no-flux boundary” (NFB)

diffu

sion

in a

ir

3. diffusion in air phase throughout

cap

waste

alluvium

NNSA/NV


Plant-Induced TransportPlant-Induced Transport

1. Plant roots uptake contaminants during growth.

2. Contaminants are redistributed within the plants.

3. Contaminants are returned to soil upon senescence.

Modeled processes:

Again: What is conservative?

cap

waste


Animal-Induced TransportAnimal-Induced Transport

Yet again: What is conservative?

Modeled processes:

1. Animals excavate subsurface bulk materials and bring them to the surface.ex

cava

tio

n

2. Burrows collapse, returning materials to the subsurface.

coll

apsecap

waste


GoldSim at the NTSGoldSim at the NTS


An example:

These bulk density data need to be turned in to an input distribution.

Stochastic ParametersStochastic Parameters

• Inventory

• Dimensions

• Material properties

• Biotic properties and rates of activities

• Human behavior

• Chemical properties


Monte Carlo SimulationMonte Carlo Simulation

• Select time stepping

• Select number of realizations

• Select seed

• Optional use of LHS

NNSA/NV

Just to be more macho with Monte Carlo, I'd suggest showing a larger number of realizations (i.e. at least 1000).


Deterministic ResultsDeterministic Results

Comparison is easy, but is it honest?

0 100 200 300 400 500 600 700 800 900 1000

time (yr)

1.00x10-04

1.00x10-03

1.00x10-02

1.00x10-01

1.00x1000

1.00x1001

1.00x1002

performance objective


0 100 200 300 400 500 600 700 800 900 1000

time (yr)

Probabilistic ResultsProbabilistic Results

Comparison is challenging, but more honest.

performanceobjective


0 100 200 300 400 500 600 700 800 900 1000

time (yr)

1.00x10-04

1.00x10-03

1.00x10-02

1.00x10-01

1.00x1000

1.00x1001

1.00x1002

Statistical SummariesStatistical Summaries

median

25%

75%

5%

95%

upper bound

lower bound

meanperformance objective


Advantages of Advantages of Probabilistic AnalysisProbabilistic Analysis

• More realistic (honest) answers

• More information for decision makers (not doing their job for them)

• Provides information for statistical comparisons with monitoring data and for value of information analysis (when to stop monitoring)

• Identification of sensitive parameters


Sensitivity Analysis 1Sensitivity Analysis 1

Sensitivity analysis provides a ranking of sensitive parameters, enhancing appreciation for their significance.

For example, dose may be driven by:1. Cap thickness2. Volume of materials excavated by ants3. Inventory of 238U4. Plant/soil concentration ratio for 99Tc


Sensitivity Analysis 2Sensitivity Analysis 2Using the MART* statistical technique,

the range over which a parameter is sensitive

can be evaluated.

*Multiple Additive Regression Trees

That’s cool!

Cap Thickness (m)

Sen

sitiv

ity I

ndex


Value of Information Value of Information AnalysisAnalysis

• Evaluate VOI from monitoring activities.

• Determine value of continued monitoring (this cannot be done with a deterministic model).

• Decide when monitoring no longer provides useful information (time to stop).


Take Home PointsTake Home Points

• Environmental modeling is most useful if done stochastically.

• Confirmation of performance assessment (through monitoring) requires statistical analysis.

• Probabilistic modeling provides a technical basis for deciding when to stop monitoring.http://www.neptuneandco.com/~jtauxe/ngwa03


Yucca Flat, Nevada:The world’s best radioactive waste disposal site.

The holes have already been “dug”!

2003 ngwa midsouth focus conference september 2003 neptune and company, inc. modeling uncertainty:...

Documents