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Adaptive global weight window generator based on particles density uniformity for Monte Carlo particles transport simulation

Peng He, Jing Song, Guangyao Sun, Shu Zhang, Lijuan Hao, Bin Wu, Liqin Hu, Yican Wu, FDS Team2021年被引用 4Nuclear FusionIF 3出版社

Variance reduction techniques are necessary for the Monte Carlo (MC) calculations in which obtaining a detailed flux distribution for a large and complex model is required. A new method for generating mesh weight window (WW) parameters is presented, named global weight window generator (GWWG). In the method, MC calculation is performed to generate the importance of each mesh voxel in the user-set region, and then the corresponding WW parameters are obtained. The importance is related to whether the simulated particles can be uniformly transported to each mesh voxel, which is called particles density uniformity. The GWWG method does not rely on user's design experience and can significantly improve the calculation efficiency. The tests for this method have been conducted on ITER reference neutronics models. In the calculation of ITER C-Lite model, the FoM was improved comparing to the analog FoM by the factor of 637.4.

日本語訳

モンテカルロ(MC)計算において、大規模かつ複雑なモデルの詳細なフラックス分布を得ることが要求される場合、分散低減技術が必要である。メッシュ・ウェイトウィンドウ(WW)パラメータを生成する新しい方法が提示され、グローバル・ウェイトウィンドウ・ジェネレータ(GWWG)と名付けられた。本方法では、MC計算を実行してユーザー設定領域内の各メッシュボクセルの重要度を生成し、その後対応するWWパラメータを取得する。重要度は、シミュレーション粒子が各メッシュボクセルへ均一に輸送され得るかどうかに関連しており、これは粒子密度均一性と呼ばれる。GWWG法はユーザーの設計経験に依存せず、計算効率を大幅に向上させることができる。本方法の試験はITER参照中性子学モデルに対して実施された。ITER C-Liteモデルの計算において、FoMはアナログFoMと比較して637.4倍に改善された。

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iter低精度(概要文一致)

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