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The purpose of this presentation is to provide an update for progress related to CritView for FY21. It includes FY21 budget summary, FY21 spending data and breakdown, highlights for FY21, highlights for the technical talks to be given at this TPR, and COVID-19 impacts to NCSP work.
Several points of collaboration between NCSP and AWE are noted, including the CIDAAS IS589 installation plan, CIDAAS testing, nuclear verification and detector physics, nuclear material control and nuclear security, and hands on criticality safety training.
Neutronics staff at CEA DES are in charge of a whole set of modeling and simulation tools for neutronics: nuclear data evaluation and processing, transport codes development, calculation sequences edition, verification, validation and uncertainty analysis. Advanced user groups are in charge of specific nuclear analysis in reactor physics, fuel cycle, criticality-safety, radiation shielding and nuclear instrumentation for CEA and its partners, at all stages of nuclear facilities life cycle. CEA is willing to participate/collaborate on the following issues: detector design, experiments, analysis and evaluation, DH validation by combining TAGS measurements with Fission Yield variance-covariance matrices.
Abstract not provided.
This presentation discusses activities related to the Nuclear Criticality Safety Program (NCSP) at Sandia National Laboratory in fiscal year 2021. This includes NCSP funding, integral experiment requests, integral experiment spending, highlights, and COVID-19 impacts.
This presentation provides an overview of the Nuclear Criticality Safety Program (NCSP), including its mission, vision, program element activities, current work, recent accomplishments, and budget/funding information.
This presentation provides background information about domestic and international nuclear criticality safety consensus standards and gives a status summary of work in progress.
This presentation provides an overview of the DOE/NNSA Nuclear Criticality Safety Program, including the program's history, mission, vision, main functions, budgetary information, accomplishments, challenges, initiatives, and current work.
This presentation provides an overview of the Nuclear Criticality Safety Program (NCSP) and its activities at Oak Ridge National Lab, including the program's history, mission and vision, accomplishments, challenges, initiatives, and tasks, as well as information regarding ORNL's NCSP budget.
This presentation provides an overview of the Nuclear Criticality Safety Program (NCSP) Nuclear Data Program, including its history, mission, vision, activities, and budgetary information.
Abstract not provided.
Abstract not provided.
The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. We demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for criticality safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.
The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. We demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for critical ity safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.
This presentation touches on the purpose of the DOE/NNSA Nuclear Criticality Safety Program Technical Program Review. This presentation also covers the background, history, mission, and vison of the organization. Slides include visual representations of the technical program element activities and the current NCSP work sites.
This presentation covers the Oak Ridge National Laboratory (ORNL) Nuclear Criticality Safety Program (NCSP) fiscal year 2022 budget summary. This presentation includes charts and graphs on budget spending and spending details for the 2022 fiscal year.
This presentation explains the meaning of the terms “Credible” and “Unlikely” for nuclear criticality safety purposes. This presentation references several terminology resources. With a focused look into ANS-8.1 Terminology. The presentation concludes with a talk on safety culture and the formality of operations program (FOP).