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Development of Artificial Neural Network Based Neutron Diffusion Equation Solver
ID：9 View Protection：ATTENDEE Updated Time：2024-09-05 09:34:20 Hits：248 Oral Presentation

Start Time：Pending（Asia/Shanghai）

Duration：Pending

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Abstract

This study presents Artificial Neural Network (ANN) based model to solve the 3-dimensional, multi-group Neutron Diffusion Equation (NDE). In this approach rigorous mathematical equations of Nodal Expansion Method (NEM) are used for developing the training dataset for the ANN model, which approximates the neutron flux through a 4th-order polynomial expansion. This approach differs from traditional methods, as ANN significantly reduces computational costs. It has been tested against 3D steady-state IAEA and 3D steady-state TWIGL benchmarks and the results show reasonable agreement with the reported results. However, the applicability of trained ANN models was also observed when the problem is significantly different from the trained data problems and hence limits its wider application for core calculations.
 
Keywords
Neutron Diffusion Equation, Nodal Expansion Method, Artificial Neural Network
Speaker
Ali Waqas
Student PIEAS

Submission Author
HASEEB UR REHMAN Pakistan Institute of Engineering and Applied Sciences
Usman Khalid PIEAS
Farhana Kausar PAEC
Masroor Ahmad PIEAS
Ali Waqas PIEAS
Aman ur Rehman PIEAS
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Important Date

  • Conference Date

    Sep 23

    2024

    to

    Sep 25

    2024

  • Sep 24 2024

    Contribution Submission Deadline

  • Sep 25 2024

    Registration deadline

Sponsored By
Harbin Engineering University (HEU)
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