legacy pra tools and methods research and development
TRANSCRIPT
1
Kurt G. VedrosCurtis Smith
Idaho National Laboratory
Legacy PRA Tools and Methods
Research and Development
2
RISA FY-21 Planned R&D Activities
• Enhanced Resilient Plant
o Support of ATF deployment by the LWR fleet
o FLEX and portable equipment implementation at NPPs
o Multi-criteria benefit evaluation (MCBE) methodology
o Terry Turbine expanded operating band
• Cost and Risk Categorization Applications
o Risk Informed plant health and asset management
• Margin Recovery and Operating Cost Reduction
o Enhanced Fire PRA modeling (FRI3D, LiDAR)
o Plant Reload Process Optimization
• Supporting Projects
o Digital I&C Risk Assessment – support of digital I&C upgrades at the LWR fleet
o Dynamic PRA and dynamic HRA (HUNTER)
o Legacy PRA Tools Enhancement
o Best Estimate plus Uncertainty (BEPU) Methodology
o RISA Toolkit V&V
RED text indicates activities that may impact or use a plant PRA
3
• Context
o Industry PRA models have become increasingly complex as their use has greatly
expanded over several decades
o Expanded use in regulatory applications has placed heavy demands on current models
to support use in plant operations and regulatory applications
o Software technology and modeling methodology hasn’t changed significantly in
decades
• Vision
o Develop technical solutions to improve the efficiency and effectiveness of PRA
methods and tools to support NPP operations, safety, and regulatory compliance
• Our Work
o Convene a group of stakeholders from across the industry to identify and prioritize key
issues related to PRA methods and tools
o Publish a research roadmap to guide the development and implementation of solutions
to key issues
Problem Statement and Vision
4
• Quantification speed to support decision-making
• Dependency modeling of human-related basic events
• Model development, maintenance, and updates
• Integration of multi-hazard models
• Other
o Improved FLEX Data for Equipment and Operator Reliability
o Expanded use of risk-informed applications
o Model improvements used for time-dependent approximations
o Sequence success term recovery
o Improved interfaces between different PRA tools
o Uncertainty analysis improvements
o Multi-unit models
o Application of artificial intelligence to support risk management
Legacy Tools Enhancement – Roadmap (2020)
5
• Quantification speed
o #1 issue identified by practitioners
• Dependency modeling of human related (HRA) basic events
o #2 issue identified by practitioners
• Integration of multi-hazard models
o Close tie-in to quantification speed and HRA dependency issues
• Create a repository of models to use for benchmarking improvements
o Generic PWR model to use as baseline for R&D purposes
• Event Tree / Fault Tree model commonly used in regulatory applications
• One-Top Fault Tree model commonly used in industry applications
• Use to quantify improvements in all areas
• Descriptions of industry and regulatory PRA approaches
Research in Progress – Issues addressed this FY
6
• Technical areas under consideration include
o High-Performance Computing and Multi-Threaded Methodologies
o Container Solving
o Parallelization using RAVEN
o Model management
Quantification speed
7
• Technical areas under consideration include
o HRA dependency modeling
• Dependency Analysis Before Quantification
• Model HRA Dependencies Similar to CCF
• Artificial Intelligence and Machine Learning to Support Dependencies
• Assign Joint HEP Minimum Value Automatically
• Capturing HRA Time Dependencies in Dynamic PRA
Dependency modeling of human related (HRA) basic events
8
• Technical areas under consideration include
o Multi-hazard model management
o Visualization and communication of results
o Ability to Efficiently Model Hazard Branches Close to 1.0
Integration of multi-hazard models
9
• Idaho State University (ISU) has created a repository for reliability/risk
reports and models
o Generic PWR model based upon SPAR approach is included
• The risk repository link is found on the ISU Nuclear Engineering web page
o https://isu.edu/ne/
• Provides publicly available information
• The report part contains approximately 500 papers
o Natural disasters
o Improving PRA
o IEEE
o Human factors
o Environmental
o Finance
o SAPHIRE and RAVEN
o Nuclear, Oil and Gas, Space, Structures, Vehicles
Repository of models to use for benchmarking improvements
10
• The current plant and regulator PRA models are very complex and time
consuming to run
o The current PRA are already oversaturated
o Plant analysts are resistant to add anything because
• The models already take too long to solve
• The models are already too difficult to manage, maintain, and understand
o It has gotten to the point that groups are duplicating the PRA to have "side" PRAs that
capture new/unique things
• Further complicates the management and maintenance
• Bring in the RISA activities from Slide 2
o Even if an activity, say Digital I&C risk/reliability or FLEX models, are correct, robust,
and technically defensible … there will be reluctance to use these in a baseline PRA
o For example, digital control system logic models would tend to be at a low level (below
the current components modeled) in the PRA which would touch many parts of the
PRA as it is solved (lower-level things trickle up through a PRA model).
• This would slow down the analysis of the model even further
Why do we need this R&D (1 of 2)
11
• We need to have R&D on legacy approaches that can solve gaps such as
those identified
o Solve faster!
o Minimize complexity!
o Present results clearly and concisely!
• We do not want to be in the position of developing all this cool technology
(flex modeling, digital IC modeling, security modeling, asset management
modeling, dependency modeling, etc.) without also understanding we need
to have the capability to add these to current PRA practices (and the
associated impacts)
Why do we need this R&D (2 of 2)
12
• Research was performed in the three areas identified as having near-term
strategic benefit to the PRA community:
o Quantification Speed of Models.
o Multi-Hazard Modeling Development, Maintenance, and Treatment.
o Human Action Dependency Analysis.
• A repository of benchmark reliability and risk models was created and
resides at Idaho State University
• Research and summarization of current practices in each of the three
areas above were performed
o Suggested improvements were proposed
o Some initial testing was performed
o Some of the improvements have cross-over implications to the other areas.
Conclusions
13
http://lwrs.inl.gov