Engineering topics

Hiromoto, Robert

Publications and source records attributed to Hiromoto, Robert.

5 records

DOE OSTI2017

Developing the User Experience for a Next Generation Nuclear Fuel Cycle Simulator (NGFCS)

This project made substantial progress on its original aim for providing a modern user experience for nuclear fuel cycle analysis while also creating a robust and functional next- generation fuel cycle simulator. The Cyclus kernel experienced a dramatic clari cation of its interfaces and data model, becoming a full- edged agent-based framework, with strong support for third party developers of novel archetypes. The most important contribution of this project to the the development of Cyclus was the introduction of tools to facilitate archetype development. These include automated code generation of routine archetype components, metadata annotations to provide re ection and rich description of each data member's purpose, and mechanisms for input validation and output of complex data. A comprehensive social science investigation of decision makers' interests in nuclear fuel cycles, and speci cally their interests in nuclear fuel cycle simulators (NFCSs) as tools for understanding nuclear fuel cycle options, was conducted. This included document review and analysis, stakeholder interviews, and a survey of decision makers. This information was used to study the role of visualization formats and features in communicating information about nuclear fuel cycles. A exible and user-friendly tool was developed for building Cyclus analysis models, featuring a drag-and-drop interface and automatic input form generation for novel archetypes. Cycic allows users to design fuel cycles from arbitrary collections of facilities for the rst time, with mechanisms that contribute to consistency within that fuel cycle. Interacting with some of the metadata capabilities introduced in the above-mentioned tools to support archetype development, Cycic also automates the generation of user input forms for novel archetypes with little to no special knowledge required by the archetype developers. Translation of the fundamental metrics of Cyclus into more interesting quantities is accomplished in the Cymetric python package. This package is speci cally designed to support the introduction of new metrics by building upon existing metrics. This concept allows for multiple dependencies and encourages building complex metrics out of incremental transformations to those prior metrics. New archetype developers can contribute their own archetype-speci c metric using the same capability. A simple demonstration of this capability focused on generating time-dependent cash ows for reactor deployment that could then be analyzed in di erent ways. Cyclist, a dedicated application for exploration of Cyclus results, was developed. It's primary capabilities at this stage are best-suited to experienced fuel cycle analysts, but it provides a basic platform for simpler visualizations for other audiences. An important part of its interface is the ability to uidly examine di erent slices of what is fundamentally a ve-dimensional sparse data set. A drag-and-drop interface simpli es the process of selecting which data is displayed in the plot as well as which dimensions are being used for

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2015

Branch-and-Bound algorithm applied to uncertainty quantification of a Boiling Water Reactor Station Blackout

Evaluation of the impacts of uncertainty and sensitivity in modeling presents a significant set of challenges in particular to high fidelity modeling. Computational costs and validation of models creates a need for cost effective decision making with regards to experiment design. Experiments designed to validate computation models can be used to reduce uncertainty in the physical model. In some cases, large uncertainty in a particular aspect of the model may or may not have a large impact on the final results. For example, modeling of a relief valve may result in large uncertainty, however, the actual effects on final peak clad temperature in a reactor transient may be small and the large uncertainty with respect to valve modeling may be considered acceptable. Additionally, the ability to determine the adequacy of a model and the validation supporting it should be considered within a risk informed framework. Low fidelity modeling with large uncertainty may be considered adequate if the uncertainty is considered acceptable with respect to risk. In other words, models that are used to evaluate the probability of failure should be evaluated more rigorously with the intent of increasing safety margin. Probabilistic risk assessment (PRA) techniques have traditionally been used to identify accident conditions and transients. Traditional classical event tree methods utilize analysts’ knowledge and experience to identify the important timing of events in coordination with thermal-hydraulic modeling. These methods lack the capability to evaluate complex dynamic systems. In these systems, time and energy scales associated with transient events may vary as a function of transition times and energies to arrive at a different physical state. Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems. Unfortunately DPRA methods introduce issues associated with combinatorial explosion of states. This study presents a methodology to address combinatorial explosion using a Branch-and-Bound algorithm applied to Dynamic Event Trees (DET), which utilize LENDIT (L – Length, E – Energy, N – Number, D – Distribution, I – Information, and T – Time) as well as a set theory to describe system, state, resource, and response (S2R2) sets to create bounding functions for the DET. The optimization of the DET in identifying high probability failure branches is extended to create a Phenomenological Identification and Ranking Table (PIRT) methodology to evaluate modeling parameters important to safety of those failure branches that have a high probability of failure. The PIRT can then be used as a tool to identify and evaluate the need for experimental validation of models that have the potential to reduce risk. Finally, in order to demonstrate this methodology, a Boiling Water Reactor (BWR) Station Blackout (SBO) case study is presented.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2014

Morphological Analysis of Zirconium Nuclear Fuel Retaining Rods Braided with SiC: Quality Assurance and Defect Identification

In the after-Fukushima world, the stability of materials under extreme conditions is an important issue for the safety of nuclear reactors. Among the methods explored currently to improve zircaloys’ thermal stability in off-normal conditions, using a protective coat of the SiC filaments is considered because silicon carbide is well known for its remarkable chemical inertness at high temperatures. A typical SiC fiber contains ~50,000 individual filaments of 5 – 10 µm in diameter. In this paper, an effort was made to develop and apply mathematical morphology to the process of automatic defect identification in Zircaloy-4 rods braided with the protective layer of the silicon carbide filament. However, the issues of the braiding quality have to be addressed to ensure its full protective potential. We present the original mathematical morphology algorithms that allow solving this problem of quality assurance successfully. In nuclear industry, such algorithms are used for the first time, and could be easily generalized to the case of automated continuous monitoring for defect identification in the future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2014

Optimization Method to Branch and Bound Large SBO State Spaces Under Dynamic Probabilistic Risk Assessment via use of LENDIT Scales and S2R2 Sets

Traditional Probabilistic Risk Assessment (PRA) methods have been developed and are quite effective in evaluating risk associated with complex systems, but lack the capability to evaluate complex dynamic systems. These time and energy scales associated with the transient may vary as a function of transition time to a different physical state. Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems, while complete, results in issues associated with combinatorial explosion. In order to address the combinatorial complexity arising from the number of possible state configurations and discretization of transition times, a characteristic scaling metric (LENDIT – length, energy, number, distribution, information and time) is proposed as a means to describe systems uniformly and thus provide means to describe relational constraints expected in the dynamics of a complex (coupled) systems. Thus when LENDIT is used to characterize four sets – ‘state, system, resource and response’ (S2R2) – describing reactor operations (normal and off-normal), LENDIT and S2R2 in combination have the potential to ‘branch and bound’ the state space investigated by DPRA. In this paper we introduce the concept of LENDIT scales and S2R2 sets applied to a branch-and-bound algorithm and apply the methods to a station black out transient (SBO).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2014

Optimized Uncertainty Quantification Algorithm Within a Dynamic Event Tree Framework

Methods for developing Phenomenological Identification and Ranking Tables (PIRT) for nuclear power plants have been a useful tool in providing insight into modelling aspects that are important to safety. These methods have involved expert knowledge with regards to reactor plant transients and thermal-hydraulic codes to identify are of highest importance. Quantified PIRT provides for rigorous method for quantifying the phenomena that can have the greatest impact. The transients that are evaluated and the timing of those events are typically developed in collaboration with the Probabilistic Risk Analysis. Though quite effective in evaluating risk, traditional PRA methods lack the capability to evaluate complex dynamic systems where end states may vary as a function of transition time from physical state to physical state . Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems. A limitation of DPRA is its potential for state or combinatorial explosion that grows as a function of the number of components; as well as, the sampling of transition times from state-to-state of the entire system. This paper presents a method for performing QPIRT within a dynamic event tree framework such that timing events which result in the highest probabilities of failure are captured and a QPIRT is performed simultaneously while performing a discrete dynamic event tree evaluation. The resulting simulation results in a formal QPIRT for each end state. The use of dynamic event trees results in state explosion as the number of possible component states increases. This paper utilizes a branch and bound algorithm to optimize the solution of the dynamic event trees. The paper summarizes the methods used to implement the branch-and-bound algorithm in solving the discrete dynamic event trees.

42 ENGINEERING↗