Edoardo Tosoni

June 4, 2018

Performance assessment of nuclear waste repositories

2

Table of contents

Part I

• Nuclear waste – sources, categories, management

• Disposal – concepts, options

• Near-surface disposal, Deep geological disposal

• Performance assessment

• Scenario analysis – general structure, pluralistic approach

Part II

• Probabilistic approach – the example of Yucca Mountain

• Pluralistic vs probabilistic approach

• Summary and conclusions

3

Part I

4

Nuclear waste

Particular characteristic ⇒ Radioactive

Radioactive decay ⇒ Waste amount decreases with time

Decay constant

Half life

After ten half lives:

𝑁𝑡 = 𝑁0𝑒−λ𝑡 λ =

1

𝑇

𝑇1 2 = 𝑇

𝑁10𝑇1 2

𝑁0= 𝑒

−λ10 −𝑙𝑛 1 2

λ = 𝑒10𝑙𝑛 1 2 = 𝑒𝑙𝑛 1 210 ≅ 0.001

𝑇1 2 = −𝑙𝑛 1 2

λ

5

Nuclear waste - Sources

Any activity involving radioactive material

Civil nuclear power energy production:

Reactor operations Spent-fuel management Decommissioning

• Ionic exchange resins

• Replaced components

• Individual protection

devices

• Spent fuel

• Vitrified waste from

reprocessing

• Structures

• Equipments

6

Nuclear waste - Categories

Two most relevant factors:

• Activity

≻ Relates to the amount of particles

that can decay, and thus emit

radiations

• Half-life

≻ Relates to the time during which the

waste exist, and thus can be

detrimental to health

Classification of radioactive waste – GSG-1, IAEA, 2009

HLW

ILW LLW

7

Nuclear waste - Management

Distinguish between:

• Storage ⇒ Temporary

• Disposal ⇒ Forever

Storage Disposal

Waste

generation

• Allow for decay

o Activity

o Temperature

• Wait for disposal solutions

8

Two fundamental disposal philosophies:

• Concentrate and confine

• Dilute and disperse

Disposal - Philosophies

Concentrate

& confine

Dilute &

disperse

Ocean dumping of nuclear

waste was banned

internationally in 1993

9

Disposal - Options

Among the studied options:

• Space disposal

• Ice-sheet disposal

• Subseabed disposal

• Transmutation

Geological disposal

• The two philosphies coexist ⇒

• Two main types:

o Near-surface

o Deep geological

• Waste is enclosed in a Russian doll-like

system of barriers

• Due to barrier degradation, some radioactivity

will escape and migrate in groundwater

Concentrate

& confine

Dilute &

disperse

Chapman & McKinley, 1987

10

Near-surface disposal

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Near-surface disposal

12

Deep geological disposal

posiva.fi

Deposition tunnels

13

Deep geological disposal – Multiple barriers: KBS3

Deposition tunnel

Deposition hole

1. Canister

2. Buffer

3. Backfill

4. Host rock

po

siv

a.f

i

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Deep geological disposal - Canister

Copper overpack Cast iron insert

Spent fuel bars vtt

.fi

posiva.fi

15

Deep geological disposal – Vertical vs. horizontal

po

siv

a.f

i

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Deep geological disposal – Projects

Olkiluoto - FIN

SITE94 - SWE

SR SITE - SWECNFWNP - CAN

Yucca Mountain - USA

Kristallin-I - SWI

KRDC – S.KOR

WIPP- USA

ANDRA - FRA

DGR - CAN

H12 – JAP

DryRun3 - UK

One has been constructed

(military waste)

17

Deep geological disposal – Conceptual scheme

Recall the two philosphies:

• Concentrate & confine

≻ The waste in disposed of under the

protection of multiple barriers

• Dilute & disperse

≻ Barriers undergo degradation:

o Mechanical strain

– Isostatic load (ice sheet)

– Sheer load (fracture displacement)

o Erosion

o Corrosion

o ...

≻ Radionuclides are released

Radionuclide release

Dose to humans

18

Performance assessment – Radiological impact

The repository will lead to some radiological impact

• Radionuclide release

• Dose to humans

In view of licensing, it is required to ascertain that such impact will be acceptably low

The level of acceptance is determined by regulation

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Performance assessment – Regulation

«…reasonable expectation that the

reasonably maximally exposed

individual receives no more than the

following annual dose from releases

from the undisturbed Yucca Mountain

disposal system: (1) 0.15 mSv for

10,000 years following disposal; and

(2) 1.0 mSv after 10,000 years, but

within the period of geologic

stability »

« The disposal of nuclear waste shall be so

designed that the radiation impacts arising

as a consequence of expected evolution: a.

the annual dose to the most exposed

individuals remains below the value of 0.1

mSv; and b. the average annual doses to other

individuals remain insignificantly low »

«…constraints for radioactive releases to the

living environment (average release of

radioactive substances per annum) referred to

in requirement 312 are as follows: a. 0.03

GBq/a for long-lived, alpha-emitting radium,

thorium, protactinium, plutonium…»

U.S. Code of Federal Regulation, Title 10, §63.311 Finland. Guide YVL D.5

20

Performance assessment – Uncertainty

Safety must be assessed over long time horizons

• Near surface ⇒ 300 y – k1,000 y

• Deep geological ⇒ 10,000 y – 1,000,000 y

Challenges:

• Site management ⇒ Heritage and communication

• Performance assessment ⇒ Uncertainty about disposal system* evolution

This aleatory uncertainty is typically tackled by Scenario analysis

Pyramids are 4,000 – 5,000 years old

* Repository + Surrounding environment = Disposal system

21

Scenario analysis – General structure

Scenario development (today’s focus)

≻ Stepwise process:

• Identification of Features, Events & Processes (FEPs)

• Construction of the system model

• Scenario generation

Consequence analysis

≻ Scenarios are analyzed quantitatively

(computer code simulations) to assess the

radiological consequences

22

Scenario analysis – Identification of the FEPs

The factors that influence the disposal system:

• Climate

• Groundwater flows

• Chemical concentrations

• Mechanical strains, etc.

List of FEPs are compiled by expert judgment:

• Existing lists or databases

• Ad hoc workshops

23

Scenario analysis – FEP lists

FEP lists vary considerably across different

Performance Assessments

• Case-to-case specificity

• Different levels of abstractions, for instance

o Advection, Heat transfer

o Water flow rate, Temperature

Recent research is trying to promote the

interpretation of the FEPs as physical quantities

Posiva, 2012a

128 FEPs

Representation of the disposal system as a set of FEPs and their

interactions (causal dependences)

Among the first attempts:

• Fault trees

• Event trees

Not very suitable:

• failure is not necessarily defined at the FEP level!

• occur-not occur modeling of FEPs is hard

24

Scenario analysis – System model

On the grounds of classical reliability analysis, FEPs

were treated as the system components, whose failure

could lead to the failure of the repository

(radionuclide release, dose to humans)

Example of chloride

concentration:

o Low values promote buffer

erosion

o High values promote canister

corrosion

o Both can lead to radionuclide

release

25

D’Alessandro & Bonne, 1981

Scenario analysis – Fault trees, event trees

Andresson et al., 1989

26

FE

Pi

FEPj

Scenario analysis – Interaction matrices, Bayesian networks

Po

siv

a, 2

01

2a

More recently:

• Interaction matrices

• Bayesian networks

27

Scenario analysis – Scenario generation

The system model serves as a driver for scenario generation

≻ Scenarios can be seen as combinations of values of the FEPs

≻ Informally speaking, FEPs are bricks to build scenarios

Approaches to scenario generation:

• Pluralistic

• Probabilistic (Part II)

28

Scenario generation – Pluralistic approach

A set of scenarios is formulated by expert judgment

Each scenario is an assumption about a combination of

values of the FEPs

The scenarios capture relevant mechanisms that cause

radionuclide release from the repository

The set of analyzed scenarios is intended to be

illustrative/representative of the possible evolutions of

the disposal system

29

Pluralistic approach - Examples

Posiva, 2013

Ondra

f-N

iras, 2

01

2

Belgium, Safety Case for Dessel

Finland, Safety Case for Olkiluoto

30

Pluralistic approach – Rationale to safety

Each scenario is checked against the regulatory limit

Po

siv

a, 2

01

2b

Time

31

Pluralistic approach – Poll on safety

Would you think the

repository is safe?

Why?

32

Pluralistic approach – Challenges

Major challenge ⇒ Comprehensiveness

≻ We recognize that we cannot analyze all possible scenarios

≻ We cannot cover the spectrum of all possible future evolutions of

the disposal system (residual uncertainty)

≻ Does this limited coverage still give us enough knowledge to support

statements about the safety of the repository?

The pluralistic approach is not fully clear about whether we know enough

• quantifying the extent to which the analyzed scenarios cover the possible futures

• characterizing the residual uncertainty about the future

33

Pluralistic approach – Comprehensiveness

Nuclear safety authorities typically react by asking for additional scenarios

ST

UK

, 2

01

5

OECD-NEA, 2012

34

Scenario generation – Probabilistic approach

The probabilistic approach has the potential to overcome these difficulties by

quantifying the uncertainty about the future, so that it can be possible to understand

whether enough is known about the safety of the repository

35

Part II

36

Probabilistic approach – Yucca Mountain

Proposed repository for HLW

Volcanic tuff, above the water table

⇒ unique!

Project interrupted in 2010 due to

political opposition

Not the only possible formalization of a

probabilistic approach

Yet illustrative

Rechard et al., 2014

The methodology is presented in Helton &

Sallaberry, 2009

37

Yucca Mountain – FEPs & system model

List of FEPs, divided into:

• Disruptive events

• Normal-evolution FEPs

Normal-evolution FEPs are simulated by

a large suite of computer codes

Calculation of the dose

Aleatory uncertainty concentrates in the

disruptive events ⇒ Stochastic modeling

Seismic

events

Volcanic

events

Early

failures

Dose to

humans

Disruptive

events

Normal-evolution FEPs

Computer codes

38

Yucca Mountain – Scenario generation

Scenario vector

For simplicity, one type of disruptive event:

Limited to

Probability space

Ideal interpretation

≻ A scenario is a point in A, that is, a realization of a

Number of occurrences

Time of j-th event

Properties of j-th

event (peak ground

velocity, duration...)

Sample space Set of

subsets

of A

Probability

distribution

over A

For instance

o Poisson process for times of occurrence

o Normal distribution for properties

Seismic events Volcanic events Early failures

39

Yucca Mountain – Consequence analysis Seismic

events

Volcanic

events

Early

failures

Dose to

humans

Disruptive

events

Normal-evolution FEPs

Computer codes

Given a scenario, the

dose is calculated by

simulation

Computer

codes

40

Yucca Mountain – Monte Carlo simulation

Procedure

1. Sample

2. Calculate

3. Repeat nS times

4. Estimate

• Distribution of

• Expected value

This is a characterization of the aleatory uncertainty

about the future

Probability

of violating

regulatory

limits

• Check against L

• Check against a max acceptable threshold

41

Yucca Mountain – Computational strategies

Straightforward MC computationally ineffective ⇒ Very large sample for adequate

representation of disruptive events

Strategy

1. Subdivide the sample space into regions

2. Calculate expected dose for individual regions

3. Aggregate afterwards

Possible subdivisions

Number of disruptive events

Type of disruptive events

Mathematically neat, but only for the

illustrative case of one type of distruptive

events

What they actually did in the Performance

Assessment, but strong assumptions

42

Yucca Mountain – Subdivision by number of events

n = 0

n = 1

n = 2

n = ...

n = 3

43

Yucca Mountain – Subdivision by type of events

Seismic

Events

Volcanic

Events Early

Failures Normal

Evolution

Seismic

Events

Volcanic

Events Early

Failures Normal

Evolution

Assumptions

• Dose from normal evolution always present

• Not included in dose from disruptive events

• No synergies among disruptive events

44

Subdivision by type of events – Dose curves

Normal evolution D

ose

Do

se

Do

se

Do

se

45

Yucca Mountain – Risk triplet

The probabilistic approach is meant to map onto the classical three questions of risk

1. What can happen? ⇒

2. How likely is it to happen? ⇒

3. What are the consequences? ⇒

With an additional question

4. What are the associated uncertainties?

46

Yucca Mountain – Epistemic uncertainty

Thus far, only aleatory uncertainty about disposal system evolution

Nevertheless, a further type of uncertainty ⇒ Epistemic

Gaps of knowledge about tools of the analysis, e.g. parameters of

• Computer codes (densities, porosities, dispersivities...)

• Probability distributions characterizing aleatory uncertainty

Characterization of epistemic uncertainty by e.g. distributions

and become distributions as well!

≻ Challenging to attain comprehensiveness

47

Pluralistic vs. Probabilistic

Pluralistic Probabilistic

Scenario

generation

Fromulation by expert

judgments

Sampling from probability

spaces

Rationale to

Safety Dose below the limit

Expected dose below the limit

Violation probability below

the threshold

48

Pluralistic vs. Probabilistic - Tensions

Practitioners are often tight to their positions

• Pluralistic ⇒ the probabilistic approach is a black box

• Probabilistic ⇒ the worst-case perspective does not build confidence on safety

Chapman et al., 1995

Goodwin et al., 1994

49

Take home

Nuclear activities produce radioactive waste that must be disposed of safely

Nuclear waste can be disposed of in geological repositories (near-surface or deep)

Large aleatory uncertainty about the disposal system evolution ⇒ Scenario analysis

Different approaches to scenario generation

• Pluralistic ⇒ Formulation of scenarios by expert judgments

• Probabilistic ⇒ Sampling scenarios from probability distributions

The key challenge is to attain comprehensiveness (hard by the pluralistic approach),

that is, to support robust statements about the safety of the repository

50

References • IAEA, Classification of Radioactive Waste, General Safety Guide, No. CSG-1. Vienna, Austria: IAEA, 2009

• Chapman NA,McKinley IG. TheGeologicalDisposal of Nuclear Waste. Chichester, UK: Wiley, 1987

• Posiva. Safety Case for the Disposal of Spent Nuclear Fuel at Olkiluoto—Features, Events and Processes. Eurajoki, Finland:Posiva Oy, 2012a

• D’Alessandro M, Bonne A. Radioactive waste disposal into a plastic clay formation. Brussels and Luxembourg: Harwood academic publishers, 1981

• Andersson J, Carlsson T, Eng T, Kautsky F, S¨oderman E, Wingefors S. The Joint SKI/SKB Scenario Development Project—SKB Report 89-35. Stockholm, Sweden: SKB, 1989

• Posiva. Safety Case for the Disposal of Spent Nuclear Fuel at Olkiluoto—Formulation of Radionuclide Release Scenarios 2012. Eurajoki, Finland: Posiva Oy, 2013

• ONDRAF/NIRAS. Selection of scenarios for long-term radiological safety assessment - Project near surface disposal of category A waste at Dessel. Brussels, Belgium: ONDRAF/NIRAS, 2012

• Posiva. Safety Case for the Disposal of Spent Nuclear Fuel at Olkiluoto—Assessment of Radionuclide Release Scenarios for the Repository System 2012. Eurajoki, Finland: Posiva Oy, 2012b

• STUK (Sateilyturvakeskus). STUK’s Review on the Construction License Stage Post Closure Safety Case of the Spent Nuclear Fuel Disposal in Olkiluoto. Helsinki, Finland: STUK, 2015

• OECD/NEA. The Long-term Radiological Safety of a Surface Disposal Facility for Low-level Waste in Belgium. OECD ,2012

• Rechard RP, Freeze GA, Perry FV. Hazards and scenarios examined for the Yucca Mountain disposal system for spent nuclear fuel and high-level radioactive waste. Reliability Engineering

and System Safety, 2014; 122:74–95

• Helton JC, Sallaberry CJ. Conceptual basis for the definition and calculation of expected dose in performance assessments for the proposed high-level radioactive waste repository at Yucca

Mountain, Nevada. Reliability Engineering and System Safety, 2009; 94:677–698

• Chapman NA, Andersson J, Robinson P, Skagius K, Wene CO, Wiborgh M, Wingefors S. Systems Analysis, Scenario Construction and Consequence Analysis Definition for SITE-94—SKI

Report 95-26. Stockholm, Sweden: SKI, 1995

• Goodwin BW, McConnell DB, Andres TH, HajasWC, LeNeveu DM, Melnyk TW, Sherman GR, Stephens ME, Szekely JG, Bera PC, Cosgrove CM, Dougan KD, Keeling SB, Kitson CI, Kummen

BC, Oliver SE, Witzke K, Wojciechowski L, Wikjord AG. The Disposal of Canada’s Nuclear Fuel Waste: Post Closure Assessment of a Reference System. Pinawa, Canada: AECL, 1994