The deformation behaviour of alloys comprising two ductile phases— I. Deformation theory

A topological transformation has been proposed, which allows a two-phase microstructure with any combination of grain-size, grain-shape, and phase distribution, to be translated into a body consisting of three well-defined microstructural elements aligned along a particular direction of interest. The resultant three-element body is shown to be mechanically equivalent to the original body along this direction. The concept of contiguity and allied topological parameters have been combined with Eshelby's continuum transformation theory to determine the internal stresses and strains, the true stress strain curve, and the in situ stress and the in situ plastic strain distribution in the three microstructural elements and thus derive the mechanical properties of the aggregate. This approach incorporates the interaction between particles of the same phase and the effect of phase distribution as well as the effect of volume fraction. Applications of the theory are given in a companion paper.     

Relationship between metal cutting performance and material properties of TiC-coated cemented carbide cutting tools

The performance of TiC-coated cemented carbide cutting tool inserts was evaluated in steel turning and cast iron milling. The machining behavior was correlated with the properties of the coating and the chemical vapor deposition parameters. It is shown that improved performance can be obtained by controlling the grain size and orientation of the coating, and by choosing appropriate parameters to minimize the formation of the substrate.     

考虑退化轨迹差异性与相似性的轴承RUL预测

轴承的个体异质性及工况差异性使得其性能退化轨迹不尽相同,导致训练轴承建立的深度学习模型与测试轴承失配.对此,提出基于卷积自编码器与自组织映射的轴承剩余使用寿命(remaining useful life,RUL)灰色预测方法.该方法引入以轴承自身监测数据为驱动的批量归一化的卷积自编码器对轴承性能退化特征进行深度提取,并结合自组织映射算法进行性能退化指标(degradation indicator,DI)自主构建.采用动态时间规划算法对各个轴承退化轨迹进行相似匹配分析,以相匹配的全寿命轴承的DI灰色模型回归曲线在寿命终点取值作为参考,进行测试轴承的失效阈值设置.以测试轴承历史DI为驱动,采用全阶时间幂灰色预测模型对测试轴承RUL进行滚动预测.实验结果表明,所提出方法在保留轴承退化趋势个体差异性的同时,能够实现轴承失效阈值自主合理设置,提高轴承RUL的预测精度.     

A novel Data-Driven framework based on BIM and knowledge graph for automatic model auditing and Quantity Take-off

Model auditing is a critical step before conducting Building Information Modeling (BIM)-based Quantity Take-off (QTO) because these models may contain various human errors and mistakes, leading to insufficient semantic information and inconsistent modeling style in BIM models. The traditional object-oriented approach has difficulties in representing unstructured BIM data (e.g., interrelationships), while rule-based methods involve tremendous human efforts to develop rule sets, lacking flexibility for different requirements. Therefore, this study aims to establish a novel data-driven framework based on BIM and knowledge graph (KG) to represent unstructured BIM data for automatic inferences of auditing results of BIM model mistakes. It starts by establishing a BIM-KG data model via identifying required information for auditing purposes. Subsequently, BIM data is automatically transformed into the BIM-KG representations, the embeddings of which are trained using a knowledge graph embedding model. Automatic mechanisms are then developed to utilize the computable embeddings to effectively identify mistake BIM elements. The framework is validated using illustrative examples and the results show that 100% mistake elements can be identified successfully without human intervention.     

Degradation analysis of dead-ended anode PEM fuel cell at the low and high thermal and pressure conditions

In this study, it is demonstrated that operation of dead-ended anode fuel cell at high temperature and pressure reduce the durability of membrane electrode assembly. In such a way that after 9000 degradation cycles, the maximum power density under H₂/O₂ gas feed mode for the aged MEA at high temperature and pressure is dropped by 38.8%. While the maximum power density drop is 27.1% for the aged MEA at low temperature and pressure. Comparison of the electrochemical impedance spectroscopy responses of MEAs shows that during aging process, the charge transfer resistance increase rate is more at higher temperature and pressure. This suggests the more severe destruction of catalyst layer at higher temperature and pressure and is in agreement with the obtained values of electrochemical surface area from the cyclic voltammetry test. In addition, the transmission electron microscopy and scanning electron microscopy images show the further degradation of cathode catalyst layer and more sever Pt agglomeration at higher temperature and pressure.     

Numerical analysis of plain journal bearing under hydrodynamic lubrication by water

The article aims to provide references for designing water-lubricated plain journal bearings. Considering the differences between the physical properties of the water and of the oil, the effects of eccentricity ratio on pressure distribution of water film are analyzed by computational fluid dynamics (CFD). Then numerical analysis of journal bearings with different dimensions is undertaken under different rotational speeds. Based on the analysis, a reference is produced for selecting the initial diameter dimension which is used to design an efficient water-lubricated plain bearing under the given load and rotational speed. At last, the reference is verified by an experimental case.     

Molecular dynamics study on the thickness of damage layer in multiple grinding of monocrystalline silicon

The molecular dynamic (MD) simulation of monocrystalline silicon under multiple grinding is carried out to study the effect of multiple grinding on the thickness of damage layer. Four grinding processes are conducted on (0 0 1) along 〈−1 0 0〉 direction. The depth of grinding of the first grinding is 20 Å. The subsequent grinding is machining on the machined surface with a damage layer left by the first grinding. The second grinding is a spark-out process and the depth of grinding of the third and fourth grinding increases by 5 Å compared with the previous grinding. The changes of structures and mechanical properties of the damage layer in the machined surface after the first grinding are investigated by coordination number (CN), the radial distribution functions (RDF) and nanoindentation. The thickness of the damage layer left by the first grinding can be reduced stably in the second and third grinding, but it will increase in the fourth grinding. Therefore, two more grinding steps between the third and fourth grinding are carried out. One is the spark-out process and the depth of grinding of the other increases by 2 Å compared with the third grinding. The results show the spark-out process can remove the springback left by the previous grinding and promote the residual compressive stress in the machined surface, which can improve the accuracy and quality of grinding. The thickness of damage layer induced by the first grinding can be reduced without new damage structures generating. However, it cannot be reduced unlimited. When the thickness of damage layer reaches half of the original thickness, a re-grinding will cause new damage structures, and the thickness of damage layer will increase. The depth of grinding is suggested to be less than half of the original damage thickness to reduce the damage layer. The research results can be applied in the ultra-precision grinding of monocrystalline silicon to control the thickness of damage layer and improve the quality of machining.     

An innovative approach for resource sharing and scheduling in a sustainable distributed manufacturing system

Secure, transparent, and sustainable distributed manufacturing system (DMS) is a pressing need for current Industry 4.0. In this paper, exchange of highly sensitive information in a more transparent and secure way and to avoid the misunderstandings and trust issues between the enterprises a smart contract based on blockchain technology has been proposed in case of a distributed manufacturing environment. Here, we used a public-permission less Ethereum platform to execute the smart contracts in the Blockchain to process the customer orders and to identify the right enterprise. Later, a multi-objective mixed-integer linear programming (MILP) model is formulated for optimal resource sharing and scheduling in a considered sustainable DMS. The objectives of the proposed model consist of simultaneously improvement of the performance measures such as makespan, machine utilization, energy consumption, and reliability. To solve this MILP model, a new Multi-objective-based Hybridized Moth Flame Evolutionary Optimization Algorithm (HMFEO) is developed and then the effectiveness of the proposed algorithm is validated with the Non-dominated Sorting Genetic Algorithm (NSGA-III). The results obtained from implementing the model using experimental data along with different cases show the efficiency and the validity of the proposed model and solution approach. Moreover, several performance indicators like hyper volume are increased by nearly 15–20 % that shows the superiority of the proposed algorithm with the NSGA-III.