Flowsheet Options for Cobalt Recovery in African Copper–cobalt Hydrometallurgy Circuits

The price of cobalt has increased by some 450% in the past two years, mainly due to increasing demand for lithium–ion batteries. With an official 2017 production of 64 kt, the Democratic Republic of Congo produces more than half of the world’s cobalt. African Copperbelt operations have traditionally focused on copper production; however, it has now become imperative to also consider cobalt recovery from these ores. A plethora of processing routes is possible. Most hydrometallurgical flowsheets recover cobalt from the raffinate of the low-grade copper solvent-extraction circuit. Downstream purification processes include sequential precipitation with a variety of reagents, solvent extraction, and ion exchange. Product choices include hydroxide, carbonate, sulfate, and metal cathode. This study assesses technical and economic advantages and limitations of various approaches to the hydrometallurgical processing of cobalt in an African context.     

平板集热器(倾角)变化工况数值模拟

运用FLUENT数值模拟软件分析了平板集热器(倾角)变化对集热器传热特性的影响,保证其结构参数不变,通过对5组不同倾角(0°、30°、45°、60°、75°)的数值模型进行非稳态模拟,对模拟数据进行分析,得出了平板集热器不同倾角对集热器传热性能变化的影响。     

Heuristic Solution to the Diffraction Problem on a Superconducting Half-Plane

Journal of Communications Technology and Electronics - Abstract—The article presents a rigorous numerical solution, using the Wiener–Hopf method, to the problem of plane wave...     

Robust optimisation of sustainable food grain transportation with uncertain supply and intentional disruptions

The proliferating need for sustainability intervention in food grain transportation planning is anchoring the attention of researchers in the interests of stakeholders and environment at large. Uncertainty associated with food grain supply further intensifies the problem steering the need for designing robust, cost-efficient and sustainable models. In line with this, this paper aims to develop a robust and sustainable intermodal transportation model to facilitate single type of food grain commodity shipments while considering procurement uncertainty, greenhouse gas emissions, and intentional hub disruption. The problem is designed as a mixed integer non-linear robust optimisation model on a hub and spoke network for evaluating near optimal shipment quantity, route selection and hub location decisions. The robust optimisation approach considers minimisation of total relative regret associated with total cost subject to several real-time constraints. A version of Particle Swarm Optimisation with Differential Evolution is proposed to tackle the resulting NP-hard problem. The model is tested with two other state-of the art meta-heuristics for small, medium, and large datasets subject to different procurement scenarios inspired from real time food grain operations in Indian context. Finally, the solution is evaluated with respect to total cost, model and solution robustness for all instances.     

Surface Integrity Assessment Upon Electric Discharge Machining of Die Steel Using Non-Destructive Magnetic Barkhausen Noise Technique

Surface integrity characterization of manufactured component is very important as it significantly affects the in-service performance of the component. Till now, surface integrity was evaluated using conventional measurement technique like microhardness tester, X-ray diffraction, optical microscopy and surface roughness tester. But, this technique being laboratory based cannot be used for in-service monitoring of the surface integrity. The present study focuses on the characterization of surface integrity upon electric discharge machined sample using non-destructive magnetic Barkhausen noise technique. Electric discharge machining was performed in die-sinking mode on die steel using copper–tungsten electrode (negative polarity). Experiment was performed by selecting different levels of peak current, gap voltage and pulse on time. Surface integrity characteristics like microhardness change, residual stress, microstructural alteration and surface roughness were analysed using microhardness tester, X-ray diffraction, optical microscopy and surface roughness tester, respectively, and were then correlated with magnetic parameter like root mean square value and peak value obtained from Barkhausen noise signal. The results show a good correlation between magnetic parameter (RMS and Peak value) of Barkhausen noise with the microhardness and surface roughness of the machined sample.

     

扩展稀疏表示稳健HRRP目标特征提取方法

为提高低信噪比下高分辨一维距离像目标识别性能，提出扩展稀疏表示的噪声稳健目标特征提取方法。本方法通过对稀疏表示的扩展，实现对目标高分辨一维距离像局部特征与全局特征的提取。其中，在训练阶段利用支持向量理论与字典学习原理，对特征提取字典进行优化提高特征向量的可分性。在测试阶段，利用因子分析模型匹配方法对去噪声字典进行优化，从而实现对噪声的有效抑制，保证了目标识别系统的噪声稳健性。利用实测数据对本方法性能进行测试，结果表明本方法可在低信噪比条件下有效地恢复目标高分辨一维距离像，并实现较高的识别正确率。     

中国废钢资源发展战略研究

 为提高中国钢铁工业的废钢比,推动钢铁工业的绿色发展,分析了中国废钢资源的概况、废钢行业技术发展现状和钢铁工业废钢利用的现状,并对中国未来废钢资源量进行预测。在此基础上,针对中国废钢资源的发展提出了3条战略判断和6条政策建议。     

F-OFDM仿真系统设计与时频同步算法

针对新一代5G波形的F-OFDM技术开展了研究,通过把一个宽带分为若干个子带,对每个子带进行滤波处理以实现更好的通信效能。基于Simulink平台进行了F-OFDM仿真系统的搭建,重点对F-OFDM符号同步方法和频偏估计方法进行了研究与仿真分析。实验结果表明,基于Chu序列相比采用PN序列可以获得更好的同步效果,基于导频的Classen频偏估计算法相比基于CP的CFO估计算法和基于训练序列的Moose估计方法可以获得更好的频偏估计效果。     

复杂难选铁矿石悬浮磁化焙烧-高效分选技术

针对传统铁矿石磁化焙烧技术与装备存在焙烧产品质量差、产能低、能耗高和环境污染严重等问题，创造性提出了一种“预热-蓄热还原-再氧化”悬浮磁化焙烧新工艺。该工艺具有原料适应性广、焙烧产品质量均匀、回收率高、生产能耗低、无污染等特点，适合处理赤铁矿、褐铁矿、菱铁矿及其混合型难选铁矿石。通过多年的潜心基础研究与技术攻关，形成了非均质矿石颗粒悬浮态流动控制、蓄热式高效低温还原、铁物相精准调控与余热同步回收等一系列关键技术，建成了500kg/h复杂难选铁矿石悬浮磁化焙烧-高效分选半工业试验平台。     

用于厚屏蔽小探测器的蒙特卡罗模拟减方差方法研究

反应堆屏蔽计算中经常出现厚屏蔽、小探测器问题，常规蒙特卡罗方法难以有效解决。基于自动重要抽样（AIS）方法，本文提出了小探测器自动重要抽样(SDAIS)方法，并针对小探测器问题，优化了AIS方法的虚粒子赌分裂算法。该方法在自主开发的蒙特卡罗屏蔽程序MCShield上进行了实现。使用NUREG/CR-6115 PWR基准题验证该方法的正确性和计算效率。结果表明，SDAIS方法可有效地解决厚屏蔽小探测器问题，相比AIS方法及传统的重要性方法，计算效率提升1~2个量级。