Exploration of High-dimensional Scalar Function for Nuclear Reactor Safety Analysis and Visualization: A User's Guide to TopoXG*

Maljovec, Dan; Wang, Bei; Pascucci, Valerio; Bremer, Peer-Timo; Pernice, Michael; Mandelli, Diego

doi:10.2172/1060988

Cited by 8 publications

(17 citation statements)

References 37 publications

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“…Furthermore, the shape of the graph indicates whether there exist stable ranges of scale to separate noise from features. The tube view (d) is similar to the visualization interfaces developed in [14] and then enhanced in [24]. The interface summarizes each Morse cell into a 1D curve using inverse linear regression in highdimensional space, which is then projected onto a viewable 3D space.…”

Section: Existing Modulesmentioning

confidence: 99%

$$\mathrm{ND}^2\mathrm{AV}$$ ND 2 AV : N-dimensional data analysis and visualization analysis for the National Ignition Campaign

Bremer

Maljovec

Saha

et al. 2015

Comput. Visual Sci.

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One of the biggest challenges in high-energy physics is to analyze a complex mix of experimental and simulation data to gain new insights into the underlying physics. Currently, this analysis relies primarily on the intuition of trained experts often using nothing more sophisticated than default scatter plots. Many advanced analysis techniques are not easily accessible to scientists and not flexible enough to explore the potentially interesting hypotheses in an intuitive manner. Furthermore, results from individual techniques are often difficult to integrate, leading to a confusing patchwork Communicated by Gabriel Wittum. Electronic supplementary materialThe online version of this article (of analysis snippets too cumbersome for data exploration. This paper presents a case study on how a combination of techniques from statistics, machine learning, topology, and visualization can have a significant impact in the field of inertial confinement fusion. We present the ND 2 AV: Ndimensional data analysis and visualization framework, a user-friendly tool aimed at exploiting the intuition and current workflow of the target users. The system integrates traditional analysis approaches such as dimension reduction and clustering with state-of-the-art techniques such as neighborhood graphs and topological analysis, and custom capabilities such as defining combined metrics on the fly. All components are linked into an interactive environment that enables an intuitive exploration of a wide variety of hypotheses while relating the results to concepts familiar to the users, such as scatter plots. ND 2 AV uses a modular design providing easy extensibility and customization for different applications. ND 2 AV is being actively used in the National Ignition Campaign and has already led to a number of unexpected discoveries.

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Section: Existing Modulesmentioning

confidence: 99%

$$\mathrm{ND}^2\mathrm{AV}$$ ND 2 AV : N-dimensional data analysis and visualization analysis for the National Ignition Campaign

Bremer

Maljovec

Saha

et al. 2015

Comput. Visual Sci.

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show abstract

“…19,996 data points 9 dimensions, i.e., 9 input variable Output variable is maximum clad temperature Using the HDViz software [12,13] (see Appendix C for details) and the from 9D-MT-all-3C dataset, we were able to obtain 3 "crystals/clusters 6 " as shown in Figure 7-1. Topological structure of the Clad max temperature as a 9-dimensional surface was characterized by a single local minima and 3 local maxima as indicated in These types of insights are important as we investigate risk-informed margins management approaches.…”

Section: Case 9d-mt-all-3cmentioning

confidence: 99%

Light Water Reactor Sustainability Program Support and Modeling for the Boiling Water Reactor Station Black Out Case Study Using RELAP and RAVEN

Mandelli

Smith

Riley

et al. 2013

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The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates. In order to evaluate the impact of these two factors on the safety of the plant, the Risk Informed Safety Margin Characterization (RISMC) project aims to provide insight to decision makers through a series of simulations of the plant dynamics for different initial conditions (e.g., probabilistic analysis and uncertainty quantification). This report focuses, in particular, on the impact of power uprate on the safety margin of a boiling water reactor. The case study considered is a loss of off-site power followed by the possible loss of all diesel generators, i.e., a station black-out (SBO) event. Analysis is performed by using a combination of thermo-hydraulic codes and a stochastic analysis tool currently under development at the Idaho National Laboratory, i.e. RAVEN.Starting from an understanding of possible SBO accident sequences for a typical boiling water reactor, we built the input file for the mechanistic thermal-hydraulics code that models system dynamics under SBO conditions. We also interfaced RAVEN with these codes so that it would be possible to run multiple RELAP simulation runs by changing specific portions of the input files. We both employed classical statistical tools, i.e. Monte-Carlo, and more advanced machine learning based algorithms to perform uncertainty quantification in order to quantify changes in system performance and limitations as a consequence of power uprate. We also employed advanced data analysis and visualization tools that helped us to correlate simulation outcomes such as maximum core temperature with a set of input uncertain parameters.Results obtained give a detailed investigation of the issues associated with a plant power uprate including the effects of SBO accident scenarios. We were able to quantify how the timing of specific events was impacted by a higher nominal reactor core power. Such safety insights can provide useful information to the decision makers to perform risk-informed margins management.ii CONTENTS

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“…Such visual interface is inherited and extended from the capabilities provided by HDViz [29] and has been previously employed for nuclear reactor analysis and visualization [50]. As shown in Figure 32 (a), the topological summary interface summarizes each Morse-Smale crystal into a 1D curve in high-dimensional space which is then projected onto a viewable 3D space.…”

Section: Visual Interfacementioning

confidence: 99%

Exploratory Nuclear Reactor Safety Analysis and Visualization via Integrated Topological and Geometric Techniques

Maljovec¹,

Wang²,

Pascucci³

et al. 2013

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Exploration of High-dimensional Scalar Function for Nuclear Reactor Safety Analysis and Visualization: A User's Guide to TopoXG*

Cited by 8 publications

References 37 publications

$$\mathrm{ND}^2\mathrm{AV}$$ ND 2 AV : N-dimensional data analysis and visualization analysis for the National Ignition Campaign

$$\mathrm{ND}^2\mathrm{AV}$$ ND 2 AV : N-dimensional data analysis and visualization analysis for the National Ignition Campaign

Light Water Reactor Sustainability Program Support and Modeling for the Boiling Water Reactor Station Black Out Case Study Using RELAP and RAVEN

Exploratory Nuclear Reactor Safety Analysis and Visualization via Integrated Topological and Geometric Techniques

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