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Conditions for Thermal Activation of Ngwo Clay as an Alternative Resource for Alumina
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作者 Udochukwu Mark Charles Nwachukwu Anyakwo +1 位作者 Okechukwu Onyebuchi Onyemaobi Chijioke Samson Nwobodo 《Natural Resources》 2019年第1期1-15,共15页
The thermal activation of Ngwo clay from southeastern Nigeria for optimal leaching of alumina was investigated. The clay assayed 24.63% Al2O3 and 52.15% SiO2, comprising mainly kaolinite mineral and free silica or qua... The thermal activation of Ngwo clay from southeastern Nigeria for optimal leaching of alumina was investigated. The clay assayed 24.63% Al2O3 and 52.15% SiO2, comprising mainly kaolinite mineral and free silica or quartz. The alumina locked up in the clay structure was rendered acid-soluble by thermal activation which transformed the clay from its crystalline nature to an amorphous, porous phase or metakaolinite. The clay samples were heated at calcination temperatures of 500°C, 600°C, 700°C, 800°C, and 900°C at holding times of 30, 60, and 90 minutes. Uncalcined clay samples and samples calcined at 1000°C (holding for 60 minutes) were used in the control experiments. After leaching the resulting clay calcines in 1 M hydrochloric acid solution at room temperature, it was observed that the clay calcines produced at 700°C (holding for 60 minutes) responded most to leaching. Samples calcined for 60 minutes also responded better than those held for 30 or 90 minutes. Based on activation energy studies, it was observed that calcines produced at 700°C (for 60 minutes) had both the highest leaching response (51.84%?after 1 hour at leaching temperature of 100°C) and the lowest activation energy of 25.03 kJ/mol. It is concluded therefore that Ngwo kaolinite clay should?be best calcined for alumina dissolution by heating up to 700°C and holding for 60 minutes at that temperature. The clay deposit has potential for use as alternative resource for alumina production in Nigeria where bauxite is scarce. 展开更多
关键词 ngwo CLAY BAUXITE KAOLINITE ALUMINA CALCINATION Thermal Activation LEACHING
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改进灰狼优化算法医疗锂电池剩余寿命预测 被引量:1
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作者 何成 刘长春 +2 位作者 武洋 吴涛 陈童 《重庆师范大学学报(自然科学版)》 CAS 北大核心 2019年第3期21-28,共8页
【目的】通过改进灰狼优化算法对医疗锂电池进行剩余寿命预测,从而保障抢救时机并减少医疗事故的目的。【方法】运用小波核极限学习机(Wavelet kernel extreme learning machine,WKELM)与小生境灰狼算法(Niche grey wolf optimization,N... 【目的】通过改进灰狼优化算法对医疗锂电池进行剩余寿命预测,从而保障抢救时机并减少医疗事故的目的。【方法】运用小波核极限学习机(Wavelet kernel extreme learning machine,WKELM)与小生境灰狼算法(Niche grey wolf optimization,NGWO)相融合的算法形成改进灰狼优化算法WKELM-NGWO算法。采用NGWO算法对WKELM参数进行优化处理,并将最大化训练集的分类准确度作为目标函数,得到寻优过程的数学模型。采用差分方式对医疗电子设备锂电池容量的时间序列进行处理,得到多维时间序列特征向量,归一化处理获得特征向量,并将其分为训练集和测试集。计算得出每只灰狼个体的适应度值fi,并对适应度值fi进行排序,适应度值fi排在前三的个体位置分别记为Xα,Xβ,Xδ。选择最优的灰狼个体位置作为WKELM参数对数据进行训练后,对心脏起搏器用锂电池和心脏除颤仪用锂电池两种锂电池测试样本进行剩余寿命预测操作。【结果】在相同的预测起始点下,WKELM-NGWO算法的均方根误差(RMSE)误差低于WKELM和NGWO算法,基于融合算法WKELM-NGWO的医疗电子设备锂电池剩余寿命(Remaining useful life)预测曲线更接近电池的退化曲线。【结论】WKELM-NGWO融合算法增强了对不同数据的适应能力,既克服了小波核极限学习机(WKELM)学习速度慢、结构不稳定的问题,也克服了小生境灰狼算法(NGWO)求解精度低、收敛速度慢从而导致跳不出局部最优解的问题。 展开更多
关键词 医疗锂电池 剩余寿命预测 小波核极限学习机 小生境灰狼算法 改进灰狼优化算法WKELM-ngwo
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