Molecular dynamics simulation (MDS) to study nanoscale machining processes

Molecular Dynamics Simulations (MDS) are constantly being used to make important contributions to our fundamental understanding of material behaviour, at the atomic scale, for a variety of thermodynamic processes. This chapter shows that molecular dynamics simulation is a robust numerical analysis tool in addressing a range of complex nanofinishing (machining) problems that are otherwise difficult or impossible to understand using other methods. For example the mechanism of nanometric cutting of silicon carbide is influenced by a number of variables such as machine tool performance, machining conditions, material properties, and cutting tool performance (material microstructure and physical geometry of the contact) and all these variables cannot be monitored online through experimental examination. However, these could suitably be studied using an advanced simulation based approach such as MDS. This chapter details how MD simulation can be used as a research and commercial tool to understand key issues of ultra precision manufacturing research problems and a specific case was addressed by studying diamond machining of silicon carbide. While this is appreciable, there are a lot of challenges and opportunities in this fertile area. For example, the world of MD simulations is dependent on present day computers and the accuracy and reliability of potential energy functions [109]. This presents a limitation: Real-world scale simulation models are yet to be developed. The simulated length and timescales are far shorter than the experimental ones which couples further with the fact that contact loading simulations are typically done in the speed range of a few hundreds of m/sec against the experimental speed of typically about 1 m/sec [17]. Consequently, MD simulations suffer from the spurious effects of high cutting speeds and the accuracy of the simulation results has yet to be fully explored. The development of user-friendly software could help facilitate molecular dynamics as an integral part of computer-aided design and manufacturing to tackle a range of machining problems from all perspectives, including materials science (phase of the material formed due to the sub-surface deformation layer), electronics and optics (properties of the finished machined surface due to the metallurgical transformation in comparison to the bulk material), and mechanical engineering (extent of residual stresses in the machined component) [110]. Overall, this chapter provided key information concerning diamond machining of SiC which is classed as hard, brittle material. From the analysis presented in the earlier sections, MD simulation has helped in understanding the effects of crystal anisotropy in nanometric cutting of 3C-SiC by revealing the atomic-level deformation mechanisms for different crystal orientations and cutting directions. In addition to this, the MD simulation revealed that the material removal mechanism on the (111) surface of 3C-SiC (akin to diamond) is dominated by cleavage. These understandings led to the development of a new approach named the “surface defect machining” method which has the potential to be more effective to implement than ductile mode micro laser assisted machining or conventional nanometric cutting.

Engineering Simulations

Over recent years, ionic liquids have emerged as a class of novel fluids that have inspired the development of a number of new products and processes. The ability to design these materials with specific functionalities and properties means that they are highly relevant to the growing philosophy of chemical-product design. This is particularly appropriate in the context of a chemical industry that is becoming increasingly focussed on small-volume, high-value added products with relatively short times to market. To support such product and process development, a number of tools can be utilised. A key requirement is that the tool can predict the physical properties and activity coefficients of multi-component mixtures and, if required, model the process in which the materials will be used. Multi-scale simulations that span density functional theory (DFT) to process-engineering computations can address the relevant time and length scales and have increased in usage with the availability of cheap and powerful computers. Herein we will discuss the area of engineering calculations relating to the design of ionic liquid processes, that is, the computational tools that bridge this gap and allow for process simulation tools to utilise and assist in the design of ionic liquids. It will be shown that, at present, it is possible to use available tools to estimate many important properties of ionic liquids and mixtures containing them with a sufficient level of accuracy for preliminary design and selection.

Modeling and simulation of bulk gallium nitride power semiconductor devices

Bulk gallium nitride (GaN) power semiconductor devices are gaining significant interest in recent years, creating the need for technology computer aided design (TCAD) simulation to accurately model and optimize these devices. This paper comprehensively reviews and compares different GaN physical models and model parameters in the literature, and discusses the appropriate selection of these models and parameters for TCAD simulation. 2-D drift-diffusion semi-classical simulation is carried out for 2.6 kV and 3.7 kV bulk GaN vertical PN diodes. The simulated forward current-voltage and reverse breakdown characteristics are in good agreement with the measurement data even over a wide temperature range.

Using virtual topology operations to generate analysis topology

Virtual topology operations have been utilized to generate an analysis topology definition suitable for downstream mesh generation. Detailed descriptions are provided for virtual topology merge and split operations for all topological entities. Current virtual topology technology is extended to allow the virtual partitioning of volume cells and the topological queries required to carry out each operation are provided. Virtual representations are robustly linked to the underlying geometric definition through an analysis topology. The analysis topology and all associated virtual and topological dependencies are automatically updated after each virtual operation, providing the link to the underlying CAD geometry. Therefore, a valid description of the analysis topology, including relative orientations, is maintained. This enables downstream operations, such as the merging or partitioning of virtual entities, and interrogations, such as determining if a specific meshing strategy can be applied to the virtual volume cells, to be performed on the analysis topology description. As the virtual representation is a non-manifold description of the sub-divided domain the interfaces between cells are recorded automatically. This enables the advantages of non-manifold modelling to be exploited within the manifold modelling environment of a major commercial CAD system, without any adaptation of the underlying CAD model. A hierarchical virtual structure is maintained where virtual entities are merged or partitioned. This has a major benefit over existing solutions as the virtual dependencies are stored in an open and accessible manner, providing the analyst with the freedom to create, modify and edit the analysis topology in any preferred sequence, whilst the original CAD geometry is not disturbed. Robust definitions of the topological and virtual dependencies enable the same virtual topology definitions to be accessed, interrogated and manipulated within multiple different CAD packages and linked to the underlying geometry.

Intelligent DMU creation: Nominal CAD model preparation for automated tolerance allocation

This paper examines the integration of a tolerance design process within the Computer-Aided Design (CAD) environment having identified the potential to create an intelligent Digital Mock-Up [1]. The tolerancing process is complex in nature and as such reliance on Computer-Aided Tolerancing (CAT) software and domain experts can create a disconnect between the design and manufacturing disciplines It is necessary to implement the tolerance design procedure at the earliest opportunity to integrate both disciplines and to reduce workload in tolerance analysis and allocation at critical stages in product development when production is imminent.
The work seeks to develop a methodology that will allow for a preliminary tolerance allocation procedure within CAD. An approach to tolerance allocation based on sensitivity analysis is implemented on a simple assembly to review its contribution to an intelligent DMU. The procedure is developed using Python scripting for CATIA V5, with analysis results aligning with those in literature. A review of its implementation and requirements is presented.