Search NASA⌕ Search
Home/Archive/DOE OSTI

DOE OSTI · 1352187

The SAS4A/SASSYS-1 Safety Analysis Code System, Version 5

Fanning, T. H.·Brunett, A. J.·Sumner, T.
View original source ↗Read source document ↗Export metadata ↓

Abstract

The SAS4A/SASSYS-1 computer code is developed by Argonne National Laboratory for thermal, hydraulic, and neutronic analysis of power and flow transients in liquidmetal- cooled nuclear reactors (LMRs). SAS4A was developed to analyze severe core disruption accidents with coolant boiling and fuel melting and relocation, initiated by a very low probability coincidence of an accident precursor and failure of one or more safety systems. SASSYS-1, originally developed to address loss-of-decay-heat-removal accidents, has evolved into a tool for margin assessment in design basis accident (DBA) analysis and for consequence assessment in beyond-design-basis accident (BDBA) analysis. SAS4A contains detailed, mechanistic models of transient thermal, hydraulic, neutronic, and mechanical phenomena to describe the response of the reactor core, its coolant, fuel elements, and structural members to accident conditions. The core channel models in SAS4A provide the capability to analyze the initial phase of core disruptive accidents, through coolant heat-up and boiling, fuel element failure, and fuel melting and relocation. Originally developed to analyze oxide fuel clad with stainless steel, the models in SAS4A have been extended and specialized to metallic fuel with advanced alloy cladding. SASSYS-1 provides the capability to perform a detailed thermal/hydraulic simulation of the primary and secondary sodium coolant circuits and the balance-ofplant steam/water circuit. These sodium and steam circuit models include component models for heat exchangers, pumps, valves, turbines, and condensers, and thermal/hydraulic models of pipes and plena. SASSYS-1 also contains a plant protection and control system modeling capability, which provides digital representations of reactor, pump, and valve controllers and their response to input signal changes.

Explore related subjects

97 MATHEMATICS AND COMPUTING

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Fanning, T. H., Brunett, A. J., Sumner, T.. 2017-01-01. The SAS4A/SASSYS-1 Safety Analysis Code System, Version 5. https://doi.org/10.2172/1352187

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

DOE OSTI2026

TANTE: Time-adaptive operator learning via neural Taylor expansion

Operator learning for time-dependent partial differential equations (PDEs) has seen rapid progress in recent years, enabling efficient approximation of complex spatiotemporal dynamics. However, most existing methods rely on fixed time step sizes during rollout, which limits their ability to adapt to varying temporal complexity and often leads to error accumulation. In this work, we propose the Time-Adaptive Transformer with Neural Taylor Expansion (TANTE), a novel operator-learning framework that produces continuous-time predictions with adaptive step sizes. TANTE predicts future states by performing a Taylor expansion at the current state, where neural networks learn both the higher-order temporal derivatives and the local radius of convergence. This allows the model to dynamically adjust its rollout based on the local behavior of the solution, thereby reducing cumulative error and improving computational efficiency. We demonstrate the effectiveness of TANTE across a wide range of PDE benchmarks, achieving superior accuracy and adaptability compared to fixed-step baselines, delivering accuracy gains of 60-80 % and speed-ups of 30-40 % at inference time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Structured illumination for surface-resolved grazing-incidence X-ray scattering

Grazing-incidence (GI) scattering techniques are widely used to characterize thin films, offering high surface sensitivity and insight into morphology and structure. However, these approaches typically provide statistical averaged information due to elongated footprint or limited spatial resolution due to beam size. Here we introduce a method that combines structured illumination with GI X-ray scattering and leverages our computational imaging approach to resolve local structural details. We demonstrate that our method captures local features of an organic semiconductor thin film without the need for sample rotation as in tomography. The method expands GI techniques from statistical averaging to high-resolution imaging, thereby providing the capability for detailed analysis of local material properties, such as domain shape, orientation and polymorphism, which are critical for advancing material design towards more efficient and tailored materials.

97 MATHEMATICS AND COMPUTING↗