Existing and New Processes for Beneficiation of Indian Iron ores

The iron ore industries of India are expected to bring new technologies to cater to the need of the tremendous increase in demand for quality ores for steel making. With the high-grade ores depleting very fast, the focus is on the beneficiation of low-grade resources. However, most of these ores do not respond well to the conventional beneficiation techniques used to achieve a suitable concentrate for steel and other metallurgical industries. The present communication discusses the beneficiation practices in the Indian context and the recent developments in alternative processing technologies such as reduction roasting, microwave-assisted heating, magnetic carrier technology and bio-beneficiation. Besides, the use of new collectors in iron ore flotation is also highlighted.     

Kinematic control of a redundant manipulator using an inverse-forward adaptive scheme with a KSOM based hint generator

This paper proposes an online inverse-forward adaptive scheme with a KSOM based hint generator for solving the inverse kinematic problem of a redundant manipulator. In this approach, a feed-forward network such as a radial basis function (RBF) network is used to learn the forward kinematic map of the redundant manipulator. This network is inverted using an inverse-forward adaptive scheme until the network inversion solution guides the manipulator end-effector to reach a given target position with a specified accuracy. The positioning accuracy, attainable by a conventional network inversion scheme, depends on the approximation error present in the forward model. But, an accurate forward map would require a very large size of training data as well as network architecture. The proposed inverse-forward adaptive scheme effectively approximates the forward map around the joint angle vector provided by a hint generator. Thus the inverse kinematic solution obtained using the network inversion approach can take the end-effector to the target position within any arbitrary accuracy.In order to satisfy the joint angle constraints, it is necessary to provide the network inversion algorithm with an initial hint for the joint angle vector. Since a redundant manipulator can reach a given target end-effector position through several joint angle vectors, it is desirable that the hint generator is capable of providing multiple hints. This problem has been addressed by using a Kohonen self organizing map based sub-clustering (KSOM-SC) network architecture. The redundancy resolution process involves selecting a suitable joint angle configuration based on different task related criteria.The simulations and experiments are carried out on a 7 DOF PowerCube? manipulator. It is shown that one can obtain a positioning accuracy of 1 mm without violating joint angle constraints even when the forward approximation error is as large as 4 cm. An obstacle avoidance problem has also been solved to demonstrate the redundancy resolution process with the proposed scheme.     

Characterization and Reduction Roasting Studies of an Iron Rich Manganese Ore

The article presents the reduction roasting followed by low intensity magnetic separation studies of a low grade Mn ore assaying 27.7% Mn and 26.1% Fe in order to obtain a Mn rich non-magnetic concentrate. The reflected light microscopic studies followed by the liberation studies of the as-received sample using quantitative mineralogical evaluation by scanning electron microscope suggested a poor liberation pattern of the constituent Mn and Fe minerals owing to a complex association of the different phases present. The reduction roasting studies carried out while varying different process parameters such as ore particle size, temperature, reductant content and residence time ended up with products containing 45–48% Mn with a Mn/Fe ratio of 5–6 at a yield of ~ 60% with the optimum level of conditions such as temperature: 800–850 °C, time: 90–120 min and charcoal: 10–12%. The scanning electron microscopy–energy dispersive X-ray spectroscopy studies of the roasted product reported manganite as the major Mn bearing phase while magnetite was found to be the major iron bearing phase.     

Visual Motor Control of a 7 DOF Robot Manipulator Using Function Decomposition and Sub-Clustering in Configuration Space

This paper deals with real-time implementation of visual-motor control of a 7 degree of freedom (DOF) robot manipulator using self-organized map (SOM) based learning approach. The robot manipulator considered here is a 7 DOF PowerCube manipulator from Amtec Robotics. The primary objective is to reach a target point in the task space using only a single step movement from any arbitrary initial configuration of the robot manipulator. A new clustering algorithm using Kohonen SOM lattice has been proposed that maintains the fidelity of training data. Two different approaches have been proposed to find an inverse kinematic solution without using any orientation feedback. In the first approach, the inverse Jacobian matrices are learnt from the training data using function decomposition. It is shown that function decomposition leads to significant improvement in accuracy of inverse kinematic solution. In the second approach, a concept called sub-clustering in configuration space is suggested to provide multiple solutions for the inverse kinematic problem. Redundancy is resolved at position level using several criteria. A redundant manipulator is dexterous owing to the availability of multiple configurations for a given end-effector position. However, existing visual motor coordination schemes provide only one inverse kinematic solution for every target position even when the manipulator is kinematically redundant. Thus, the second approach provides a learning architecture that can capture redundancy from the training data. The training data are generated using explicit kinematic model of the combined robot manipulator and camera configuration. The training is carried out off-line and the trained network is used on-line to compute the joint angle vector to reach a target position in a single step only. The accuracy attained is better than the current state of art.     

An Adaptive Secure and Efficient Routing Protocol for Mobile Ad Hoc Networks

The rapidly emerging wireless service requirements and deployment demands over last few decades necessitates the application of Mobile Ad hoc Networks in many areas. These application areas vary from social networks to safety-critical domains such as environmental monitoring, disaster rescue operations, military communications, etc. The potency of the ad hoc network deployment in a specific context is significantly affected by the underlying routing protocol. Hence, developing an efficient and secure routing protocol for MANETs is an important task in order to achieve the service level requirements and to satisfy the deployment demands effectively. However, development of such routing protocol is a challenging problem due to the inherent characteristics of ad hoc networks: frequent topology changes, open wireless medium, and limited resource constraints, etc. In addition, the stringent requirements: mobility, performance, security, trust and timing constraints, etc. add complexity to this problem. In this paper, we present an adaptive routing protocol for MANETs, which dynamically configures the routing function with respect to the metrics: (1) the varying requirement parameters and (2) the contextual features as per the desired application context. The requirement models include various performance, security, and functional parameters. On the other hand, the contextual features include mobility of nodes/groups of nodes, nodes’ trust values, resource constraints of nodes, geographical context, roles of individual nodes etc. Our routing protocol is evaluated with extensive simulation test cases and the efficacy of the protocol is reported.

     

Investigation on the Coal-Based Direct Reduction of Mill Scale Pellets: Statistical Modeling and Characterization Studies

Transactions of the Indian Institute of Metals - The feasibility of producing direct reduced iron from pellets made up of mill scale by utilizing coal as a reductant has been investigated. The...     

印度一水硬铝石样品中氧化铁相的矿物学、解离和浸出特性（英文）

利用磁选和浸出技术从印度一水硬铝石样品中除铁,采用扫描电镜、电子探针显微分析仪和X射线衍射等定量矿物学评价技术进行深入的矿物学表征研究。结果表明,极细的赤铁矿颗粒与其他几种矿物相以复杂的方式结合在一起;即使粒度小于38μm,仍有约60%的赤铁矿未被解离出来;这个粒度也是物理分离过程去铁的极限。湿式强磁选研究表明,只有49%的铁可被除去。进一步的草酸浸出研究表明,在固液比0.05:1、温度90°C、时间120 min、酸浓度1 mol/L的条件下,可除去约76%的铁。铁在草酸中的溶解受化学反应控制,计算的活化能为35.15 k J/mol。     

Influence of reactors,microbial carbohydrate uptake,and metabolic pathways on ethanol production from grass biomass: A review

Grasses are considered to be potential lignocellulosic feedstock for renewable and sustainable biofuels such as bioethanol. However, the process involved, ie, pretreatment, enzymatic saccharification, and fermentation in conversion of these lignocellulosic biomass to bioethanol, remains expensive and at present is not affordable for industrial production. Thus, the present review assesses the influence of the recent technologies that can be employed for the bio‐refinery based pretreatment and enzymatic hydrolysis of grass biomass using advanced bioreactors. Since plant extracts have been seen to enhance the glucose uptake, an experiment was implemented to elucidate the role of plant extracts (bark extracts of Xylocarpus granatum) on glucose uptake capacity of microorganisms like Saccharomyces cerevisiae, Pichia sp., and Zymomonas mobilis and their subsequent ethanol production capability from glucose and xylose sugars. The results of these experiments indicated that supplementation of plant extracts promoted both glucose and xylose uptake in S. cerevisiae and Pichia sp. as compared with the control and Z. mobilis strain. Further, as Pichia sp. exhibited good uptake ability for both glucose and xylose, a model was proposed focusing on the gene silencing and operon concept in Pichia sp. for preferential pentose utilization during the fermentation of grass biomass to bioethanol.