1. A System Analysis Code to Support Risk-Informed Safety Margin Characterization: Rationale, Computational Platform and Development Plan Nam Dinh, Vince Mousseau and Robert Nourgaliev

2. Content Rationale Computational Platform Development Plan

3. Rationale Risk-Informed safety margin characterization (RISMC) –LWR Sustainability (safety margins) –Support for PRA –Increased role of non-DBA sequences –Multi-physics (TH, NK, CC, FP, SM) coupling –Sensitivity analysis, uncertainty quantification –Integrated safety assessment – Search for vulnerability Passive safety design –Natural circulation –Reactor-to-containment connectivity –Multidimensional behavior –Long transients

4. CapacityLoad CL UQ Surprise Safety Margin Power Uprate, Higher Burnup

5. Variability of Input System Transient Multi-physics Computational Expenses Modeling uncertainty Engineering Analysis (large # calculations) Confidence (error bar) in calculated results

6. (Dimensions, Components, Heterogeneity) Physics Modeling (Simplification) “First principles” Computing ExpensesValidation Adequacy [CFD-RANS] System codes Separate Effects Simplified Plant, “Detail” Processes System Analysis Real-time Simulators System Complexity CGM- and AMR-based System Analysis Vehicle

7. Experiments (SET, IET) Computational Platform

8. 0D 1D 3D CG 3D  Coarse-grain simulations effectively capture large-scale flow patterns  CFD flow solver transports SGS (EANS, LANS, DM)  Under-resolved flow structures is effectively represented by subgrid-scale (SGS) closure  Exploring Three CGM Theoretical Concepts  Eulerian-Average Navier-Stokes (LES, RANS)  Lagrangian-Average Navier-Stokes (LANS/  -NS)  Discrete Modeling  Database  CGM Adaptive Model Refinement

9. Attributes under Consideration Fully implicit, nonlinearly (tightly) coupled multi-physics (neutronics, thermal hydraulics, structural mechanics, fuels) High order accurate in time and in space, robust numerics Parallel, high-performance computing Adaptive Model Refinement (0D, 1D, 3D based on Error Estimation) Built-in sensitivity analysis (Uncertainty Quantification, Quantitative PIRT) CFD-based Coarse-Grain Modeling

10. Structural Mechanics Core Neutronics Multi-physics, Multi-scale Algorithms Fuel Performance Thermal Hydraulics Sensitivity Analysis, Uncertainty Quantification Advanced Solution Methods (Solvers) Computable Meshing HPC: High Performance Computing Plant I&C Active Components Passive Components Fluids, Materials Properties Governing Physics ●●●●● Models Computational Infrastructure Heterogeneous System ●●●●● Components Pump, Valve, etc. Pipe, Tanks, etc. ●●● e.g., Coolant Chemistry, FPT PC clusters and up

11. Nuclear Systems Safety Analysis Transient/Accident Scenario Multi-physics Plant Model Thermal-Hydraulics System Model Coarse-Grain (SGS) Closure Laws Core Neutronics Model Single-Physics Plant Discrete Modeling (Meshing) ●●● Databases Data Management Correlations HPC-Generated High-Fidelity IE and SE “Data” Advanced Diagnostics IE and SE Experiments Local Parameters Data Mining Uncertainty Quantification Safety Margin (with UQ) Adequacy of plant discrete model, model fidelity level, and closure data support Uncertainty Acceptable? Model Fidelity Selection Yes No Identify weakness ? Discrete Model ? Model Fidelity ? Closure Data Use Sensitivity Analysis (SA) ●●●

12. V&V DemonstrationDevelopment Research R7 Project Work Domain Multiple Physics Heterogeneous System ( Multiple Components) Computational Methods Complexity Investigate selected topics (in the Development’s three dimensions; see above), which present major obstacles to achieving the R7 code operability and intended functionality. Early applications of the R7 code to a selected set of plant transient and accident scenarios, to examine and demonstrate the code operability, intended features and V&V strategy. R7 Code V&V Planning (System Safety Objectives) Requirements for database content and management Consistency Forecast of future data availability and quality Acquisition of the R7’s key support data Development Plan

13. V&V DemonstrationDevelopment Research CAML and HPC support RELAP users Training R7 “activists” Contributors Modules INL and non-INL Aligned Projects Methods, Models Testing ETFD Database CFD Database New Experiments Advanced Diagnostics Data Management R7 Project Leverage Domain R7 Project Work Domain

14. Formation Phase (I)Maturation Phase (II) R7 RD&D and V&V Project  Broaden scope  Refinement Applications Expansion (III) Year 1Year 2Year 3Year 4Year 5Year 6Year 7  Extend V&V V&V RD&D

15. Engineering Analysis Modeling (Subgrid Closure) Database (SE, IE ) V&V Higher Fidelity Models Advanced Diagnostics, DNS Labs, HPC

16. Coarse-Grain Closure Models System-Scale Models Plant Dynamics Multi-Scale Treatment Separate-Effect (SE) Benchmarks Integral-Effect (IE) Benchmarks Multi-physics (MP) Benchmarks Multi-Physics Treatment Industry-Wide Databases (CFD, ETFD, Plant Data) Verification Validation Reactor Measurements Advanced Diagnostics IE and SE Experiments HPC-Generated High-Fidelity IE and SE “Data” MP Verification Multi-Tier Diagnostics & Computer-Aided V&V Strategy for R7 Code

17. Concluding Remarks The project aims to develop a next-generation system safety code that enables the nuclear power industry to meet requirements in future engineering analysis of plant transients and accidents. The project’s (Phase I) technical objectives are (i) to develop the code’s computational frameworks and basic methods/models/components, (ii) to establish the code’s V&V methodology (requirements and feasibility), and (iii) to demonstrate the code’s intended capabilities through investigation of selected safety-significant transients in advanced reactor systems. The guiding principle and major challenges in the development are selecting an appropriate level of fidelity and ensuring consistency between the level of detail in mathematical modeling, numerical solution methods and the evolving state-of- the-art capabilities in experimental diagnostics.