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The process of reloading pattern optimization was carried out in two states.
Loading pattern optimization was performed using SGHSNE package for some test cases to present the SGHS algorithm capability in converging to near optimal loading pattern.
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Well pattern optimization is an important part of oil field development design.
Fuel reload pattern optimization is a crucial fuel management activity in nuclear power reactors.
As the size of the array is increased, the computational complexity and time for pattern optimization are increased drastically.
The fuel loading pattern optimization is an important process in the refueling design of a nuclear reactor core.
A methodology specifically suited for micro-protruded pattern optimization is designed, leading to 73% enhancement in thermal performance respect to commercially available heat sinks, at fixed costs.
Well type and pattern optimization is the key technology to improve single well estimated reserves and recovery factor and to achieve effective field development.
The two main goals in core fuel loading pattern design optimization are maximizing the core effective multiplication factor (Keff) in order to extract the maximum energy, and keeping the local power peaking factor (Pq) lower than a predetermined value to maintain fuel integrity.
Two main goals in core fuel loading pattern design optimization are maximizing the core effective multiplication factor in order to extract the maximum energy, and keeping the local power peaking factor lower than a predetermined value to maintain the fuel integrity.
The ABS pattern optimization problem is shown to be NP-hard in a multi-cell full buffer traffic scenario [23].
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