Diana Cuervo

Assessment of CTF Boiling Transition and Critical Heat Flux Modeling Capabilities Using the OECD/NRC BFBT and PSBT Benchmark Databases

Over the last few years, the Pennsylvania State University (PSU) under the sponsorship of the US Nuclear Regulatory Commission (NRC) has prepared, organized, conducted, and summarized two international benchmarks based on the NUPEC data—the OECD/NRC Full-Size Fine-Mesh Bundle Test (BFBT) Benchmark and the OECD/NRC PWR Sub-Channel and Bundle Test (PSBT) Benchmark. The benchmarks’ activities have been conducted in cooperation with the Nuclear Energy Agency/Organization for Economic Co-operation and Development (NEA/OECD) and the Japan Nuclear Energy Safety (JNES) Organization. This paper presents an application of the joint Penn State University/Technical University of Madrid (UPM) version of the well-known sub-channel code COBRA-TF (Coolant Boiling in Rod Array-Two Fluid), namely, CTF, to the steady state critical power and departure from nucleate boiling (DNB) exercises of the OECD/NRC BFBT and PSBT benchmarks. The goal is two-fold: firstly, to assess these models and to examine their strengths and weaknesses; and secondly, to identify the areas for improvement.

Selected Papers from OECD-NEA PSBT Benchmark

Historically, the prediction of safety margins has been based on system level thermal-hydraulic calculations employing suitable empirical formulations for assembly specific geometries and fuel-element grid spacers. These works have assessed response, margins, and consequences for the system based on one-dimensional two-fluid or drift-flux type thermalhydraulics formulations with fuel-vendor specific hydraulic losses and heat transfer characteristics for various fuel assemblies, including the so-called hot channel. Analysis of the hot channel gives important information on flow rates, fuel element centerline temperature, fuel sheath temperature, and margin to the departure from nucleate boiling. Given the reliance of the above approaches on empirical formulations obtained from complex and often difficult experiments, there is significant interest in obtaining reliable and accurate results from computation tools which employ more fundamental empirical relationships which can be obtained from subsets of the domain or from other scaled experiments.