ASME Section III Division 4 Fusion Energy Devices Code Rules

2020 ◽  
Author(s):  
William K. Sowder
Keyword(s):  
Fusion Energy ◽  
Energy Devices

2025 Nuclear Code: The Vision for the Future of ASME Nuclear Codes and Standards

2018 ◽  
Author(s):  
Dale E. Matthews ◽  
Ralph S. Hill ◽  
Charles W. Bruny
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
New Technologies ◽  
Fusion Energy ◽  
Life Cycle Management ◽  
Economic Benefits ◽  
Plant Design ◽  
Element Analysis ◽  
Energy Devices ◽  
The Future

ASME Nuclear Codes and Standards are used worldwide in the construction, inspection, and repair of commercial nuclear power plants. As the industry looks to the future of nuclear power and some of the new plant designs under development, there will be some significant departures from the current light water reactor (LWR) technology. Some examples are gas-cooled and liquid metal-cooled high temperature reactors (HTRs), small modular reactors (SMRs), and fusion energy devices that are currently under development. Many of these designs will have different safety challenges from the current LWR fleet. Variations of the current LWR technology are also expected to remain in use for the foreseeable future. Worldwide, many LWRs are planned or are already under construction. However, technology for construction of these plants has advanced considerably since most of the current construction codes were written. As a result, many modern design and fabrication methods available today, which provide both safety and economic benefits, cannot be fully utilized since they are not addressed by Code rules. For ASME Nuclear Codes and Standards to maintain and enhance their position as the worldwide leader in the nuclear power industry, they will need to be modernized to address these items. Accordingly, the ASME Nuclear Codes and Standards organizations have initiated the “2025 Nuclear Code” initiative. The purpose of this initiative is to modernize all aspects of ASME’s Nuclear Codes and Standards to adopt new technologies in plant design, construction, and life cycle management. Examples include modernized finite element analysis and fatigue rules, and incorporation of probabilistic and risk-informed methodology. This paper will present the vision for the 2025 ASME Nuclear Codes and Standards and will discuss some of the key elements that are being considered.

ASME Division IV Magnetic Confinement Fusion Energy Devices

2010 ◽  
Author(s):  
William Sowder ◽  
Richard W. Barnes
Keyword(s):  
Work Group ◽  
Fusion Energy ◽  
Magnetic Confinement ◽  
Vacuum Vessel ◽  
Metallic Materials ◽  
Support Structures ◽  
Magnetic Confinement Fusion ◽  
Energy Devices ◽  
Confinement Fusion ◽  
Group Fusion

There is an on-going effort within the ASME Section III Codes and Standards organization approved by the ASME Board of Nuclear Codes and Standards to develop rules for the construction of fusion-energy-related components such as vacuum vessel, cryostat and superconductor structures and their interaction with each other. These rules will be found in Division IV of Section III entitled “Magnetic Confinement Fusion Energy Devices (BPV III)”. Other related support structures, including metallic and non-metallic materials, containment or confinement structures, fusion-system piping, vessels, valves, pumps, and supports will also be covered. The rules shall contain requirements for materials, design, fabrication, testing, examination, inspection, certification, and stamping. The formation of a new Work Group Fusion Energy Devices that will develop these rules is just beginning to develop its membership and future working group support structures.

scholarly journals Encoder–decoder neural network for solving the nonlinear Fokker–Planck–Landau collision operator in XGC

2021 ◽  
Vol 87 (2) ◽  
Author(s):  
M. A. Miller ◽  
R. M. Churchill ◽  
A. Dener ◽  
C. S. Chang ◽  
T. Munson ◽  
...  
Keyword(s):  
Neural Network ◽  
Particle Density ◽  
Fusion Energy ◽  
Collision Operator ◽  
Training Data ◽  
Advanced Technique ◽  
Energy Devices ◽  
The Neural Network ◽  
Plasma Species ◽  
Fokker Planck

An encoder–decoder neural network has been used to examine the possibility for acceleration of a partial integro-differential equation, the Fokker–Planck–Landau collision operator. This is part of the governing equation in the massively parallel particle-in-cell code XGC, which is used to study turbulence in fusion energy devices. The neural network emphasizes physics-inspired learning, where it is taught to respect physical conservation constraints of the collision operator by including them in the training loss, along with the $\ell _2$ loss. In particular, network architectures used for the computer vision task of semantic segmentation have been used for training. A penalization method is used to enforce the ‘soft’ constraints of the system and integrate error in the conservation properties into the loss function. During training, quantities representing the particle density, momentum and energy for all species of the system are calculated at each configuration vertex, mirroring the procedure in XGC. This simple training has produced a median relative loss, across configuration space, of the order of $10^{-4}$ , which is low enough if the error is of random nature, but not if it is of drift nature in time steps. The run time for the current Picard iterative solver of the operator is $O(n^2)$ , where $n$ is the number of plasma species. As the XGC1 code begins to attack problems including a larger number of species, the collision operator will become expensive computationally, making the neural network solver even more important, especially since its training only scales as $O(n)$ . A wide enough range of collisionality has been considered in the training data to ensure the full domain of collision physics is captured. An advanced technique to decrease the losses further will be subject of a subsequent report. Eventual work will include expansion of the network to include multiple plasma species.

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