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Uncertainty quantification of unconfined spill fire data by coupling Monte Carlo and artificial neural networks
Journal of Nuclear Science and Technology ( IF 1.2 ) Pub Date : 2024-01-27 , DOI: 10.1080/00223131.2024.2310564
Elvan Sahin 1 , Brian Lattimer 1 , Mohammad Amer Allaf 2 , Juliana Pacheco Duarte 2
Affiliation  

Due to the complexity of spill fire, predicting heat release rate (HRR) is a challenging aspect, therefore, identifying key contributors to uncertainty is essential to develop reliable models for f...

中文翻译:

通过蒙特卡罗和人工神经网络耦合无侧限泄漏火灾数据的不确定性量化

由于泄漏火灾的复杂性,预测热释放率 (HRR) 是一个具有挑战性的方面,因此,确定不确定性的关键因素对于开发可靠的模型至关重要。
更新日期:2024-01-28
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