Towards a Risk-Based, Cost- Optimized Approach for the ...

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Towards a Risk-Based, Cost-Optimized Approach for the Design of Nuclear Facilities

Chandu BolisettiFacility Risk Group

Idaho National Laboratory

DOE NPH WorkshopRockville, MD

MotivationTo address the large capital costs of nuclear power plants• Costs are dominated by civil works and

not the nuclear reactor and turbine island

• Site-specific load cases like seismic play a key role

"The Future of Nuclear Energy in a Carbon Constrained World - An Interdisciplinary MIT Study.” (2018). MIT Energy Initiative, Massachusetts Institute of Technology, Cambridge, MA, USA.

How do we reduce seismic costs?• Reducing conservatisms in

demand calculation• Seismic isolation and

standardization of designs• Risk-based design

(MITEI, 2018)

Presenter

Presentation Notes

Another recommendation is that seismic load case should be considered for much earlier in the design process than right now. The risk-based design process involves looking at risk estimates and likely accident sequences earlier in the design process so that better decisions can be made. Looking at cost at this point might help reduce costs.

Approaches to Reducing Seismic Costs • Nonlinear soil-structure interaction

– Obtain accurate estimates of seismic demands by accounting for all the nonlinearities in the soil-structure system

– Extend the current SPRA approach to include nonlinear response through enhanced fragility calculations

• Seismic isolation– Drastically reduce seismic demands and

seismic risk– Enable standardization of design by

adapting the isolation system to the site and keeping the superstructure design

Com

pone

nt p

roba

bilit

y of

failu

re

0.1 0.2 0.3 0.4 0.5 0.6

Peak ground acceleration (g)

0

2

4

6

8

10

12

14

16

18

20

Cos

t inc

reas

e ov

er b

asel

ine

(%)

Overnight capital cost (OCC)

Structures, systems and components (SSCs) cost

Conventional: INL Conventional: LANL

11%

14%

4%

7% 7%

3%

Isolated

9%

Yu et al., 2018

Bolisetti et al., 2017

Presenter

Presentation Notes

Not just NLSSI but also reducing conservatisms in general, such as in ground motion prediction, risk assessment, concrete response, etc.

Current projectGoals• Develop approaches to optimize the seismic design of advanced

reactor NPPs for both safety and cost using – seismic base isolation– seismic isolation of individual components– risk+cost optimization

Tasks• Implement seismic isolator models in MASTODON• Build NLSSI + seismically isolated models of the NPPs and calculate cost and

risk savings• Build representative PRA models of the NPPs and optimize SSC seismic

design using risk+cost-based design and strategic use of seismic isolation• Develop software tools for optimization

Presenter

Presentation Notes

Tasks are divided into 2 approaches for this project. Describe both approaches.

Seismic Isolator Models in MASTODON

Lead-RubberBearing

Kumar et al (2014)

Friction-PendulumBearing

Kumar et al (2015)

Presenter

Presentation Notes

Physical behaviors modeled in LR isolator: Buckling and cavitation in axial, hysteretic response in shear, P-∆ effects, and the interaction between vertical and horizontal response. In FP bearings, dependence of coefficient of friction on velocity, pressure, temperature, etc.

Risk+Cost-Based Design

Analyze

Design

Calculate cost

Calculate risk

Risk - informed design

Risk+cost - based design

• Advance from risk-informed design to a risk-based design

• Optimize the design for both safety AND cost

• Enable strategic use of risk mitigation techniques such as seismic isolation and other energy dissipation mechanisms, as well as NLSSI modeling, to reduce capital cost while meeting safety goals

• Provide a decision-making tool and not just an analysis tool

Implementing Risk+Cost Optimization in MASTODON

SPRA Process

Probabilistic sampling of the input model

Running simulations

Calculating fragilities

Fault-tree analysis and risk calculation

• Inputs seismic hazard curve for time-based assessment

• Sampling using LHC, Monte Carlo, etc., and automatically parallelized

Preprocessing

Simulation

Postprocessing

• Inputs: SSC capacities, fault trees and event trees

• Outputs: Component fragilities, minimal cutsets, associated probabilities, component importance measures, system fragilities and system risk(benchmarked with Saphire)

Automation of SPRA calculations

Presenter

Presentation Notes

Automation of SPRA and pre and post processing will help analysts and designers account for seismic risk early on in the design process. The post processing can be used with other software as well. MASTODON is modular enough that different parts of the code can be isolated and used differently.

Design optimization - Problem

DesignChange

CapacitiesUse

Isolation

Demands Fragilities Risk

Cost Cost functionMinimize

ConstraintStay just below risk target

Optimize

Presenter

Presentation Notes

This is the optimization problem. It is definitely a blackbox problem for realistic cases. Therefore we will pursue blackbox algorithms Design doesn’t just depend on risk, there will be several other factors. These factors can be accounted for by providing specific ranges in the capacities, or other sorts of constraints.

Design optimization – Sample resultsPump fails

to start

Seismic failure

Power failure

Dist. Panel fail (seismic)

Dist. Panel fail (power)

Block wall fail (seismic)

Switch gear fail (seismic)

Battery fail (seismic)

1

2 3

4

Presenter

Presentation Notes

Ran a very case to understand how the problem works. Only changing fragilities (func of PGA) The model: Minimal cutsets Costs associated with the SSCs as a function of their design capacities. If the capacity is increased, cost will increase and risk will decrease. If the capacity is decreased risk will increase and cost will decrease.


to start

Seismic failure

Power failure






1

2 3

4

Am = 3.49g cost = $12M0.2% of total risk

Am = 1.67g cost = $7M 22% of total risk

Am = 1.75g cost = $8.8M


Am = 3.50g cost = $18M

InitialSystem risk = 4e-6Total cost = $51M

~0% of total risk


to start

Seismic failure

Power failure






1

2 3

4

Am = 3.49g cost = $12M

Am = 1.67g cost = $7M

Am = 1.75g cost = $9M

Am = 2.2g cost = $5M

Am = 3.5g cost = $18M

InitialSystem risk = 4e-6Total cost = $51M

FinalSystem risk = 7e-8Total cost = $47M

Am = 1.47g cost = $12M20% of total risk


Am = 1.0g cost = $8M

Am = 1.0g cost = $15M

Am = 2.7g cost = $5M40% of total risk

~0% of total risk

Presenter

Presentation Notes

The idea is to show the process. Other examples might show better results.

Future Work• Gather realistic fault-tree and

cost data from industry partners

• Use particle-swarm optimization • Blackbox optimization with

constraints• Ideal for parallel computing• Well studied; plenty of

literature and examples available

• Start with DAKOTA

• Optimization code will be independent of seismic analysis software

en.wikipedia.org/wiki/Particle_swarm_optimization

Acknowledgments

• Saran Bodda and Abhinav Gupta, NCSU

• Sharath Parsi and Andrew Whittaker, UB

• Will Hoffman and Justin Coleman, INL

• Advanced nuclear industry partners

Questions?

Email:[email protected]

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