Search NASA⌕ Search

DOE OSTI · 1030306

Modeling Impact-Induced Reactivity Changes Using DAG-MCNP5

Abstract

There is a long literature studying the criticality of space reactors immersed in water/sand after a launch accident; however, most of these studies evaluate nominal or uniformly compacted system configurations. There is less research on the reactivity consequences of impact, which can cause large structural deformation of reactor components that can result in changes in the reactivity of the system. Predicting these changes is an important component of launch safety analysis. This paper describes new features added to the DAG-MCNP5 neutronics code that allow the criticality analysis of deformed geometries. A CAD-based solid model of the reactor geometry is used to generate an initial mesh for a structural mechanics impact calculation using the PRONTO3D/PRESTO continuum mechanics codes. Boundary conditions and material specifications for the reactivity analysis are attached to the solid model that is then associated with the initial mesh representation. This geometry is then updated with the deformed finite element mesh to perturb node coordinates. DAG-MCNP5 was extended to accommodate two consequences of the large structural deformations: dead elements representing fracture, and small overlaps between adjacent volumes. The dead elements are removed during geometry initialization and adjustments are made to conserve mass. More challenging, small overlaps where adjacent mesh elements contact cause the geometric queries to become unreliable. A new point membership test was developed that is tolerant of self-intersecting volumes, and the particle tracking algorithm was adjusted to enable transport through small overlaps. These new features enable DAG-MCNP5 to perform particle transport and criticality eigenvalue calculations on both deformed mesh geometry and CAD geometry with small geometric defects. Detailed impact simulations were performed on an 85-pin space reactor model. In the most realistic model that included NaK coolant and water in the impact simulation, the eigenvalue was determined to increase 2.7% due to impact.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Smith, Brandon M., Wilson, Paul Philip Hood. 2011-02-10. Modeling Impact-Induced Reactivity Changes Using DAG-MCNP5. https://www.osti.gov/biblio/1030306

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

KEEP EXPLORING

Related reports

Pulsed-Neutron Experiments at the Inherently Safe Subcritical Assembly

The pulsed neutron technique is a powerful, dynamic method to assay the reactivity of a multiplying system. This work presents the novel application of the pulsed neutron technique to the Inherently Safe Subcritical Assembly, an experimental configuration accepted by the International Criticality Safety Benchmark Evaluation Project Handbook. The experiments were replicated with COG11.3, a continuous-energy Monte Carlo code. The pulsed neutron data were analyzed using the Sjöstrand and Gozani area-ratio methods and by extracting the prompt neutron decay constant. Subsequent static k-eigenvalue and 𝛼-eigenvalue simulations were also performed for the same configurations. Neutron detector dead-time effects from the experiments were corrected using the Backwards Extrapolation Method and shown to have a negligible impact on the estimated reactivities. The results highlight that capturing time-dependent effects like delayed neutron precursor buildup are essential to accurately reproduce experimental results. They also highlight the importance of shielding the detectors from generator source neutrons in deeply subcritical configurations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Machine Learning–Based Condition Monitoring of a Circulating Water System of a Canadian Nuclear Plant

With the need to maintain long-term reliable energy using nuclear power plants, there is an underlying demand to ensure that the maintenance of plant components and systems is also done in an efficient and cost-effective manner. One way to achieve this is by moving from time-based maintenance to condition-based maintenance. The research presented in this paper focuses on applying statistical and machine-learning-based methods to capture anomalies within data for fault detection to further develop into condition monitoring. This paper focuses on system data for a circulating water system (CWS) of a pressurized heavy-water reactor for detecting anomalies. The different methodologies used for detecting and capturing anomalies in the CWS data are matrix profile, density-based spatial clustering of applications with noise (DBSCAN), and support vector machines (SVMs). Matrix profile and DBSCAN are used to distinguish between normal data and anomalous data. This paper presents a hybrid method using DBSCAN and SVM when a portion of the data is used for DBSCAN to generate clusters. This portion of data is then used to train the SVM along with the clusters generated by DBSCAN as output. SVM is then tested on unseen data as a predictive tool, which can work in real time to categorize data points as either normal or anomalous. This paper presents results that show the high accuracies of DBSCAN and SVM in capturing anomalies within the data for a CWS for fault detection. Thus, the maintenance plan would be focused on component condition rather than a time-based schedule by switching to an automated system to identify and predict faults within a CWS.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

SCALE HTR-PROTEUS Benchmark Model

This dataset contains input and result files of computational simulations of HTR-PROTEUS benchmark with the latest version of SCALE code system. The simulations cover criticality control rod worth calculations as well as sensitivity analysis and uncertainty quantification. Users wanting to reproduce results from this dataset are required to obtain a license to the SCALE code system for which details on the distribution can be found here: https://www.ornl.gov/scale/releases

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗