Instituto de Biotecnología, Facultad de Ingeniería, UNSJ, San Juan, Argentina.
Instituto de Investigación y Desarrollo en Ingeniería de Procesos, Biotecnología y Energías Alternativas, PROBIEN (CONICET-UNCo), Neuquén, Argentina.
J Environ Manage. 2021 Mar 1;281:111915. doi: 10.1016/j.jenvman.2020.111915. Epub 2021 Jan 9.
An artificial neural network (ANN) model was developed to simulate the convective drying process of watermelon rind pomace used in the fabrication of non-traditional flour. Also, the drying curves obtained experimentally were fitted with eleven different empirical models to compare both modeling approaches. Lastly, to reduce the required fossil fuel in the convective drying process, two types of solar air heaters (SAH) were presented and experimentally evaluated. The optimization of the ANN by a genetic algorithm (GA) resulted in an optimal number of neurons of nine (9) for the first hidden layer and ten (10) for the second hidden layer. Also, the ANN performed better than the best fitted empirical model. Simulations with the trained ANN showed very promising generalization capabilities. The type II SAH showed the best performance and the highest air temperature it reached was 45 °C. The specific energy consumption (SEC) needed to dry the watermelon rind at this temperature and the CO emissions were 609 kWh.kg and 318 kg CO.kWh, respectively. Using the type II SAH, this energy amount would be saved without CO emissions. To reach higher drying temperatures the combination of the SAH and the electrical convective dryer is possible.
开发了一个人工神经网络 (ANN) 模型来模拟用于制造非传统面粉的西瓜皮残渣的对流干燥过程。此外，还将实验获得的干燥曲线拟合到十一个不同的经验模型中，以比较两种建模方法。最后，为了减少对流干燥过程中所需的化石燃料，提出并实验评估了两种类型的太阳能空气加热器 (SAH)。通过遗传算法 (GA) 对 ANN 进行优化，得到了第一个隐藏层 9 个神经元和第二个隐藏层 10 个神经元的最佳神经元数量。此外，ANN 的性能优于最佳拟合的经验模型。经过训练的 ANN 的模拟显示出非常有前途的泛化能力。类型 II 的 SAH 表现出最好的性能，达到的最高空气温度为 45°C。在这个温度下干燥西瓜皮所需的比能（SEC）和 CO 排放量分别为 609 kWh.kg 和 318 kg CO.kWh。使用类型 II 的 SAH，可以在不排放 CO 的情况下节省这些能源。为了达到更高的干燥温度，可以将 SAH 和电对流干燥器结合使用。
