Modeling and simulation challenges pursued by the Consortium for Advanced Simulation of Light Water Reactors (CASL)

Abstract

The Consortium for the Advanced Simulation of Light Water Reactors (CASL), the first Energy Innovation Hub of the Department of Energy, was established in 2010 with the goal of providing modeling and simulation (M&S) capabilities that support and accelerate the improvement of nuclear energy's economic competitiveness and the reduction of spent nuclear fuel volume per unit energy, and all while assuring nuclear safety. To accomplish this requires advances in M&S capabilities in radiation transport, thermal-hydraulics, fuel performance and corrosion chemistry. To focus CASL's R&D, industry challenge problems have been defined, which equate with long standing issues of the nuclear power industry that M&S can assist in addressing. To date CASL has developed a multi-physics "core simulator" based upon pin-resolved radiation transport and subchannel (within fuel assembly) thermal-hydraulics, capitalizing on the capabilities of high performance computing. CASL's fuel performance M&S capability can also be optionally integrated into the core simulator, yielding a coupled multi-physics capability with untapped predictive potential. Material models have been developed to enhance predictive capabilities of fuel clad creep and growth, along with deeper understanding of clad oxidation and hydrogen pickup. Understanding of corrosion chemistry (e.g., CRUD formation) has evolved at all scales: micro, meso and macro. CFD R&D has focused on improvement in closure models for subcooled boiling and bubbly flow, and the formulation of robust numerical solution algorithms. For multiphysics integration, several iterative acceleration methods have been assessed, illuminating areas where further research is needed. Finally, uncertainty quantification and data assimilation techniques, based upon sampling approaches, have been made more feasible for practicing nuclear engineers via R&D on dimensional reduction and biased sampling. Industry adoption of CASL's evolving M&S capabilities, which is in progress, will assist in addressing long-standing and future operational and safety challenges of the nuclear industry.

The Virtual Environment for Reactor Applications (VERA): Design and architecture

“…A primary goal of CASL is to develop an understanding of several key "Challenge Problems" for the nuclear industry. The CASL Challenge Problems are described in detail in [12], and each requires a specific combination of physics, spatial and temporal resolution, and level of 5 coupling/feedback between components. For example, the Pellet-Clad Interaction (PCI) Challenge Problem requires two tools: a scoping tool and a high-fidelity tool.…”

“…The effort required for these activities is often underestimated and unappreciated.  Challenge problems defined by subject matter experts (partners in the nuclear industry, in the case of CASL) are essential for defining scope and requirements, and for conveying impact to stakeholders and the community [12]. However, in general they are too complex to be used to drive development.…”

Verification of bubble tracking method and DNS examinations of single- and two-phase turbulent channel flows

“…Departure from nucleate boiling (DNB) is the limiting critical heat flux phenomena for the majority of accidents that are postulated to occur in pressurized water reactors (PWR) [2]. As one of the major modeling and simulation (M&S) challenges pursued by CASL, the prediction capability is being developed for the onset of DNB utilizing multiphase-CFD (M-CFD) approach.…”

Optimizing the RMC Code Using the Decay Chain Method for Large-Scale Decay Calculations

“…There is a growing interest in high-fidelity simulations using detailed reactor-core models where the fuel region can be divided into millions of regions. Several full-core benchmarks have been developed, such as the Virtual Environment for Reactor Applications (VERA) (Godfrey, 2014) of the Consortium for Advanced Simulation of Light Water Reactors (CASL) (CASL, 2014;Turinsky and Kothe, 2016), the Nuclear Energy Agency (NEA) Monte Carlo performance benchmark problem (H&M) (Hoogenboom and Martin, 2009) and the MIT PWR (BEAVRS) benchmark (Horelik and Herman, 2012). One common feature of these benchmarks is the huge number of burn-up regions, ranging from thousands to millions of regions.…”