Fundamental Study on Scheduling of Inspection Process for Fast Reactor Plants

Ito, Mari; Hashidate, Ryuta; Takahashi, Keita; Yada, Hiroki; Takaya, Shigeru

doi:10.1109/iiai-aai50415.2020.00157

Cited by 2 publications

(3 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, the maintenance schedule planned to investigate the constraints should be updated appropriately according to the progress of the plant design. Therefore, an automatic maintenance scheduling module for components was developed to facilitate the estimation of plant availability and identify design issues for efficient maintenance (Suzuki, 2020;Hashidate, 2023). The current prototype module can provide a maintenance schedule for multi-maintenance cycles maximizing the plant availability and satisfying constraints for simplified examples based on the prototype SFR of MONJU in Japan by using branch and bound search, which is one of the typical approaches for the integer programming problem.…”

Section: Optimization Process For the Maintenance Schedule Of The Plantmentioning

confidence: 99%

“…ARKADIA can be a specific tool for the optimization of the safety margin to achieve the innovation of codes and standards systems using risk insights. As a global trend, the RIPB approach has been introduced to the safety design of advanced nuclear power plants (U.S. NRC, 2007and 2020, NEI, 2019. The effective allocation of resources to reduce the total plant risk may be developed by introducing the RIPB approach to the component design.…”

Section: Prospects In Arkadia Developmentmentioning

confidence: 99%

See 1 more Smart Citation

Development of element functions and design optimization procedures for knowledge- and AI-aided advanced reactor lifecycle optimization method, ARKADIA

TANAKA,

ENUMA,

OKANO

et al. 2024

Mechanical Engineering Journal

View full text Add to dashboard Cite

Japan Atomic Energy Agency (JAEA) is developing an artificial intelligence (AI) aided integrated digital system: "Advanced Reactor Knowledge-and AI-aided Design Integration Approach through the whole plant lifecycle (ARKADIA)", to provide the best possible solutions for challenges arising during the design process, safety assessment, and operation of a nuclear plant over its life cycle. Until 2023, the platform for a common function and subsystems, namely ARKADIA-Design for design study, ARKADIA-Safety for safety assessment, and ARKADIA-knowledge management system (KMS) for the knowledge base, are separately being developed. This paper describes the development concepts of the platform, the progress of the application study of design optimization in ARKADIA-Design, the progress of optimization model development and optimization functionality based on AI technology in ARKADIA-Safety, and the structure of the knowledge base and application of AI technology to ARKADIA-KMS. In subsystems, necessary modules and process integration to obtain an optimal solution in a designated problem of plant design have been advanced. For further development, a strategy for unifying the subsystems with the AI-aided platform into one system, ARKADIA, and the extension of capabilities of the numerical analyses and evaluation technologies required for plant design until 2028 are presented.

show abstract

Section: Optimization Process For the Maintenance Schedule Of The Plantmentioning

confidence: 99%

Section: Prospects In Arkadia Developmentmentioning

confidence: 99%

Development of element functions and design optimization procedures for knowledge- and AI-aided advanced reactor lifecycle optimization method, ARKADIA

TANAKA,

ENUMA,

OKANO

et al. 2024

Mechanical Engineering Journal

View full text Add to dashboard Cite

show abstract

“…A clustering scheduling strategy maps the grouped tasks into an infinite number of computational units. In the steps of the clustering algorithm, each step of the clustering is an arbitrary task that may not be the ready task, so it is necessary to go back in each group to select the ready task for scheduling, where there is [16] formalized the scheduling problem as an integer planning clustering problem with grouped clustering scheduling [17]. Scheduling algorithms based on replication strategies are also task computational resources are unbounded and replication-based strategies use redundant tasks to reduce communication overhead [18,19].…”

Section: Related Workmentioning

confidence: 99%

Improved Scheduling Algorithm for Synchronous Data Flow Graphs on a Homogeneous Multi-Core Systems

Wang

2022

Algorithms

View full text Add to dashboard Cite

In order to accelerate the execution of streaming applications on multi-core systems, this article studies the scheduling problem of synchronous data flow graphs (SDFG) on homogeneous multi-core systems. To describe the data flow computation process, we propose the SDAG (Super DAG) computation model based on the DAG model combined with data-driven thoughts. Further, we analyze the current common SDFG scheduling algorithms and propose an improved SDFG scheduling algorithm, LSEFT (level-shortest-first-earliest-finish time). The LSEFT algorithm uses an inverse traversal algorithm to calculate the priority of tasks in the task-selection phase; the shortest-job-priority earliest-finish-time policy is used in the processor selection phase to replace the original long job priority policy. In the experimental part, we designed an SDFG random generator and generated 958 SDFGs with the help of the random generator as test cases to verify the scheduling algorithm. The experimental results show that our improved algorithm performs well for different numbers of processor cores, especially for 8 cores, where the speedup of our improved algorithm improves by 10.17% on average.

show abstract

Fundamental Study on Scheduling of Inspection Process for Fast Reactor Plants

Cited by 2 publications

References 4 publications

Development of element functions and design optimization procedures for knowledge- and AI-aided advanced reactor lifecycle optimization method, ARKADIA

Development of element functions and design optimization procedures for knowledge- and AI-aided advanced reactor lifecycle optimization method, ARKADIA

Improved Scheduling Algorithm for Synchronous Data Flow Graphs on a Homogeneous Multi-Core Systems

Contact Info

Product

Resources

About