Dataset for Off-centered stagnation-controlled strategy mechanism on heat transfer aspects of chemically reactive non-Newtonian nanofluid

The current data is associated with the study on the off-centered stagnation-controlled strategy mechanism on a non-Newtonian chemically reactive nanofluid using an artificial neural network analysis. When evaluating the mass and heat transport of fluid flow, the importance of both active and passive control of nanoparticles is considered. It is designed to monitor the numerical approximation of the heat transfer rate for different parameters in both control scenarios through testing, training, and validation. The Excel file contains the numerically generated Nusselt number values corresponding to varying values of the heat source/sink parameter and Brownian motion parameter. It also contains the Nusselt number values predicted using the ANN model, together with the associated error and absolute error values for both active and passive control cases.本数据集关联一项基于人工神经网络（Artificial Neural Network，ANN）分析的非牛顿化学反应性纳米流体偏心滞止控制策略机制研究。该研究在评估流体流动的质量与热量输运特性时，同步考量了纳米颗粒主动控制与被动控制的重要性。本数据集旨在通过测试、训练与验证流程，监测两种控制场景下不同参数对应的传热速率数值近似结果。该Excel文件包含了数值生成的努塞尔数（Nusselt number）数值，其对应不同热源/热汇参数与布朗运动（Brownian motion）参数的取值；同时还收录了基于人工神经网络模型预测得到的努塞尔数数值，以及主动、被动两种控制场景下对应的伴随误差与绝对误差数值。