Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.     

A new one-phase material model for the numerical prediction of critical material flow conditions in thixoforging processes

Thixoforging allows one-step forming processes of near-net shape components having excellent mechanical properties. However, the high sensitivity of thixoforging regarding process conditions requires precise modelling and determination of process related parameters. At the same time, simple numerical design proves challenging because of the inaccuracy of existing one-phase material models regarding the shear thinning flow behaviour of semi solid metals. Consequently, this paper deals with the development of a new one-phase material model providing a more precise simulation of materials’ shear rate dependency. By using this model, simulations could be performed, which allowed the prediction of solidification and flow-related component defects.     

基于遗传运算法QSPR模型预测润滑剂在铜箔表面的润湿能力

采用静态悬滴法研究了润滑剂中脂肪酸、醇类和酯类添加剂在压延铜箔表面的接触角和润湿行为。利用半经验的量子化学方法计算了这些化合物的一些结构参数对其接触角进行了研究。利用遗传运算(GFA)统计分析方法，通过分子折射率和几种结构参数研究了其定量结构-性质关系。结果表明计算的量子参数可用于预测润滑剂在压延铜箔表面的接触角和润湿能力。这些润滑剂的接触角是其粘度、界面张力和物理化学参数的函数。其中起到主要作用的参数中，分子的折射率、分子的折射率、分子的弹性、总分子质量、溶剂表面积、元素计数、总能量和偶极子最关键。值得注意的是，润滑剂在压延铜箔表面的研究使润湿理论能精确到微观尺度，这为预测润滑剂在压延铜箔表面的润湿能力提供了新的见解。     

An integrated DEMATEL-MMDE-ISM based approach for analysing the barriers of IoT implementation in the manufacturing industry

Incorporation of smart devices within the older framework has brought along significant challenges. This paper presents a detailed analysis of the barriers faced during the implementation of Internet of Things (IoT) within the manufacturing sector. In addition, the authors aim to obtain a hierarchical structure, which will help the policymakers to identify the most crucial barriers enabling them to make an informed decision. With the help of databases like Scopus, Web of Science, etc. a comprehensive list of 22 barriers was initially obtained. This list was further narrowed down to 10 critical barriers. The first step of the analysis involved the application of Decision Making Trial and Evaluation Laboratory (DEMATEL) technique, which quantifies the influence of the barriers amongst one another. Maximum Mean De-Entropy (MMDE) technique is then used to obtain a scientific threshold value, which is later used in the Interpretive Structural Modelling (ISM) technique from which a hierarchical structure of the barriers is obtained. The results of this study are expected to highlight the most crucial barriers wherein the researchers and practitioners can focus their strategic efforts. This will facilitate the addressal of implicit issues while implementing IoT Techniques in the manufacturing industry.     

Optimisation of the fuelling of hydrogen vehicles using cascade systems and ejectors

The present study investigates the replacement of expansion valves, used in the cascade system of hydrogen fuelling stations, by a series of ejectors. The major advantage of using ejectors is to recover part of the kinetic energy lost during the expansion of a high-pressure primary flow, in order to entrain a lower pressure secondary flow; thus resulting in a more efficient fuelling.Firstly, a quasi-steady 1-D simulation model of the ejector was calibrated using computational fluid dynamics in terms of the main geometry and pressure conditions.Secondly, the quasi-steady 1-D model of the ejector was used in a dynamic model of the hydrogen fuelling station, in order to investigate the influence of its geometry on the transient fuelling performances. Different fuelling scenarios were explored with varying number of buffer tanks in the cascade system of the fuelling station, and different initial pressures in the vehicle's tank. The results show that the replacement of the expansion valve by an ejector may reduce the energy consumption for hydrogen compression by up to 6.5% using two buffer tanks in the cascade system. On the other hand, increasing the number of buffer tanks reduces the energy savings as the driving pressure ratio decreases.     

Modelling,simulation and identification of an engine air path electromechanical actuator

This paper deals with the modelling and the identification of an electromechanical Diesel engine actuator. The studied Bosch GPA-S actuator is designed for swirl/tumble flaps to control the air amount entering into the cylinder. This study aims to design a complete simulator that reproduces, with sufficient accuracy, the actuator dynamics taking into account the effects of the friction phenomenon. Hence, an overview of the actuator structure and its operation principle is first given. Then, its mathematical model as well as the nonlinearity, related to its behaviour, is discussed. Next, three identification procedures, which allow estimating both the system parameters and the friction model coefficients, are introduced. Finally, simulation results, using MATLAB, and experimental results, using LabVIEW, are presented demonstrating the effectiveness of the proposed techniques.     

Predicting the tensile creep of concrete

Over a four year period, six phases of testing were performed to observe the influence of age at loading, applied stress level, mix composition and relative humidity on the tensile creep of concrete. From these investigations it was possible to develop a model which allowed the prediction of tensile creep based on a knowledge of the compressive strength of the concrete (determined at the age of loading), the applied stress level and the relative humidity. Subsequently, this model was validated using the results from three independent investigations. Compressive creep as well as tensile creep was also obtained. This allowed a comparison of compressive creep with tensile creep and illustrated that on the basis of equal stresses, tensile creep is on average between 2 and 3 times greater than compressive creep (the maximum ratio is in excess of 8). For this investigation, however, on the basis of stress/strength ratio the difference between tensile and compressive creep is less significant. Considering a simply supported flexural reinforced concrete element, the investigation suggests that it is unwise to consider actual compressive creep equal to actual tensile creep as is often the case in design practice.     

A specific energy-based size reduction model for batch grinding ball mill

A particle size reduction model has been developed as the first component of an upgraded ball mill model. The model is based on a specific energy-size reduction function, which calculates the particle breakage index, t₁₀, according to the size-specific energy, and then calculates the full product size distribution using the t₁₀–t_n relationships and the mass-size balance approach. The model employs an ore-specific and size-dependent breakage function, whose parameters are independently measured with a fine particle breakage characterisation device, the JKFBC. This has effectively overcome the limitation of using a default breakage appearance function for all ores in the perfect mixing ball mill model. Since the ore-specific characteristics and the machine-related specific energy parameters are mechanistically incorporated in the size reduction model, it has the capability to predict size reduction in response to changes in the ball mill feed breakage characteristics and the operation-related specific energy.     

Dynamic energy and mass balance model for an industrial alkaline water electrolyzer plant process

This paper proposes a parameter adjustable dynamic mass and energy balance simulation model for an industrial alkaline water electrolyzer plant that enables cost and energy efficiency optimization by means of system dimensioning and control. Thus, the simulation model is based on mathematical models and white box coding, and it uses a practicable number of fixed parameters. Zero-dimensional energy and mass balances of each unit operation of a 3 MW, and 16 bar plant process were solved in MATLAB functions connected via a Simulink environment. Verification of the model was accomplished using an analogous industrial plant of the same power and pressure range having the same operational systems design. The electrochemical, mass flow and thermal behavior of the simulation and the industrial plant were compared to ascertain the accuracy of the model and to enable modification and detailed representation of real case scenarios so that the model is suitable for use in future plant optimization studies. The thermal model dynamically predicted the real case with 98.7 % accuracy. Shunt currents were the main contributor to relative low Faraday efficiency of 86 % at nominal load and steady-state operation and heat loss to ambient from stack was only 2.6 % of the total power loss.     

Mathematical modelling and simulation of nitrite hydrogenation in a membrane microreactor

Nitrite hydrogenation using heterogeneous catalysis is an important process for purification of wastewater or potable water. The main aim of this study is to explore a new mechanistic model and simulation for a heterogeneously catalysed reaction in a microporous catalytic layer. The system studied involves a liquid solution containing certain amount of nitrite, and a membrane reactor in which the nitrite penetrates into the catalytic layer to react with hydrogen. The developed model considers coupling between equations of momentum transfer in free and porous media and convection-diffusion of nitrite. It was found that there is great agreement between measured data and modelling values. Increasing velocity was the main reason for reduction of nitrite conversion and also there was a slight increase in nitrite conversion with increasing the thickness and porosity of catalytic layer. Furthermore, it was found that the diffusion mass transfer mechanism is favourable for nitrite hydrogenation while convective mass transfer of fluid flow has negative impact on nitrite hydrogenation.