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 plantsā¢ Costs are dominated by civil works and
not the nuclear reactor and turbine island
ā¢ Site-specific load cases like seismic play a key role
"The Future of Nuclear Energy in a Carbon Constrained World - An Interdisciplinary MIT Study.ā (2018). MIT Energy Initiative, Massachusetts Institute of Technology, Cambridge, MA, USA.
How do we reduce seismic costs?ā¢ Reducing conservatisms in
demand calculationā¢ Seismic isolation and
standardization of designsā¢ Risk-based design
(MITEI, 2018)
Approaches to Reducing Seismic Costs ā¢ Nonlinear soil-structure interaction
ā Obtain accurate estimates of seismic demands by accounting for all the nonlinearities in the soil-structure system
ā Extend the current SPRA approach to include nonlinear response through enhanced fragility calculations
ā¢ Seismic isolationā Drastically reduce seismic demands and
seismic riskā 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
Current projectGoalsā¢ Develop approaches to optimize the seismic design of advanced
reactor NPPs for both safety and cost using ā seismic base isolationā seismic isolation of individual componentsā risk+cost optimization
Tasksā¢ Implement seismic isolator models in MASTODONā¢ Build NLSSI + seismically isolated models of the NPPs and calculate cost and
risk savingsā¢ Build representative PRA models of the NPPs and optimize SSC seismic
design using risk+cost-based design and strategic use of seismic isolationā¢ Develop software tools for optimization
Seismic Isolator Models in MASTODON
Lead-RubberBearing
Kumar et al (2014)
Friction-PendulumBearing
Kumar et al (2015)
Risk+Cost-Based Design
Analyze
Design
Calculate cost
Calculate risk
Risk - informed design
Risk+cost - based design
ā¢ Advance from risk-informed design to a risk-based design
ā¢ Optimize the design for both safety AND cost
ā¢ 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
ā¢ Provide a decision-making tool and not just an analysis tool
Probabilistic sampling of the input model
Running simulations
Calculating fragilities
Fault-tree analysis and risk calculation
ā¢ Inputs seismic hazard curve for time-based assessment
ā¢ Sampling using LHC, Monte Carlo, etc., and automatically parallelized
Preprocessing
Simulation
Postprocessing
ā¢ Inputs: SSC capacities, fault trees and event trees
ā¢ Outputs: Component fragilities, minimal cutsets, associated probabilities, component importance measures, system fragilities and system risk(benchmarked with Saphire)
Automation of SPRA calculations
Design optimization - Problem
DesignChange
CapacitiesUse
Isolation
Demands Fragilities Risk
Cost Cost functionMinimize
ConstraintStay just below risk target
Optimize
Design optimization ā 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
Design optimization ā 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
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 = 2.2g cost = $5M 78% of total risk
Am = 3.50g cost = $18M
InitialSystem risk = 4e-6Total cost = $51M
~0% of total risk
Design optimization ā 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
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 = 1.7g cost = $7M 40% 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
Future Workā¢ Gather realistic fault-tree and
cost data from industry partners
ā¢ Use particle-swarm optimization ā¢ Blackbox optimization with
constraintsā¢ Ideal for parallel computingā¢ Well studied; plenty of
literature and examples available
ā¢ Start with DAKOTA
ā¢ Optimization code will be independent of seismic analysis software
en.wikipedia.org/wiki/Particle_swarm_optimization
Acknowledgments
ā¢ Saran Bodda and Abhinav Gupta, NCSU
ā¢ Sharath Parsi and Andrew Whittaker, UB
ā¢ Will Hoffman and Justin Coleman, INL
ā¢ Advanced nuclear industry partners