Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

https://escholarship.org/content/qt8rf718jm/qt8rf718jm.pdf?t=krnesf

Recent Advances in Mechanical Micromachining

As companies strive to develop artefacts intended for services instead of traditional sell-off, new challenges in the product development process arise to promote continuous improvement and increasing market profits. This creates a focus on product life-cycle components as companies then make life-cycle commitments, where they are responsible for the function availability during the extent of the life-cycle, i.e. functional products. One of these life-cycle components is manufacturing; therefore, companies search for new approaches of success during manufacturability evaluation already in engineering design. Efforts have been done to support early engineering design, as this phase sets constraints and opportunities for manufacturing. These efforts have turned into design for manufacturing methods and guidelines. A further step to improve the life-cycle focus during early engineering design is to reuse results and use experience from earlier projects. However, because results and experiences created during project work are often not documented for reuse, only remembered by some people, there is a need for design support. Knowledge engineering (KE) is a methodology for creating knowledge-based systems, e.g. systems that enable reuse of earlier results and make available both explicit and tacit corporate knowledge, enabling the automated generation and evaluation of new engineering design solutions during early product development. There are a variety of KE-approaches, such as knowledge-based engineering, case-based reasoning and programming, which have been used in research to develop design for manufacturing methods and applications. There are, however, opportunities for research where several approaches and their interdependencies, to create a transparent picture of how KE can be used to support engineering design, are investigated. The aim of the research presented in this thesis is to create new methods for design for manufacturing, by using several approaches of KE, and find the beneficial and less beneficial aspects of these methods in comparison to each other and earlier research. This thesis presents methods and applications for design for manufacturing using KE. KE has been employed in several ways, namely rule-based, rule-, programmingand finite element analysis (FEA)-based, and ruleand plan-based, which are tested and compared with each other. Results show that KE can be used to generate information about manufacturing in several ways. The rule-based way is suitable for supporting life-cycle commitments, as engineering design and manufacturing can be integrated with maintenance and performance predictions during early engineering design, though limited to the firing of production rules. The rule-, programmingand FEA-based way can be used to integrate computer-aided design tools and virtual manufacturing for non-linear stress and displacement analysis. This way may also bridge the gap between engineering designers and computational experts, even though this way requires a larger effort to program than the rule-based. The ruleand planbased way can enable design for manufacturing in two fashions – based on earlier manufacturing plans and based on rules. Because earlier manufacturing plans, together with programming algorithms, can handle knowledge that may be more intricate to capture as rules, as opposed to the time demanding routine work that is often automated by means of rules, several opportunities for designing for manufacturing exist.

Methods and Applications

Ultra-precision grinding is primarily used to generate high quality and functional parts usually made from hard and difficult to machine materials. The objective of ultra-precision grinding is to generate parts with high surface finish, high form accuracy and surface integrity for the electronic and optical industries as well as for astronomical applications. This keynote paper introduces general aspects of ultra-precision grinding techniques and point out the essential features of ultra-precision grinding. In particular, the keynote paper reviews the state-of-the-art regarding applied grinding tools, ultra-precision machine tools and grinding processes. Finally, selected examples of advanced ultra-precision grinding processes are presented.

Ultra-precision grinding

Molecular dynamics (MD) simulation has enhanced our understanding about ductile-regime machining of brittle materials such as silicon and germanium. In particular, MD simulation has helped understand the occurrence of brittle–ductile transition due to the high-pressure phase transformation (HPPT), which induces Herzfeld–Mott transition. In this paper, relevant MD simulation studies in conjunction with experimental studies are reviewed with a focus on (i) the importance of machining variables: undeformed chip thickness, feed rate, depth of cut, geometry of the cutting tool in influencing the state of the deviatoric stresses to cause HPPT in silicon, (ii) the influence of material properties: role of fracture toughness and hardness, crystal structure and anisotropy of the material, and (iii) phenomenological understanding of the wear of diamond cutting tools, which are all non-trivial for cost-effective manufacturing of silicon. The ongoing developmental work on potential energy functions is reviewed to identify opportunities for overcoming the current limitations of MD simulations. Potential research areas relating to how MD simulation might help improve existing manufacturing technologies are identified which may be of particular interest to early stage researchers.

/pdf/diamond-machining-of-silicon-a-review-of-advances-in-h5mvksdo94.pdf

Diamond machining of silicon: A review of advances in molecular dynamics simulation

In this experimental study, diamond turning of single crystal 6H-SiC was performed at a cutting speed of 1 m/s on an ultra-precision diamond turning machine (Moore Nanotech 350 UPL) to elucidate the microscopic origin of ductile-regime machining. Distilled water (pH value 7) was used as a preferred coolant during the course of machining in order to improve the tribological performance. A high magnification scanning electron microscope (SEM FIB- FEI Quanta 3D FEG) was used to examine the cutting tool before and after the machining. A surface finish of Ra=9.2 nm, better than any previously reported value on SiC was obtained. Also, tremendously high cutting resistance was offered by SiC resulting in the observation of significant wear marks on the cutting tool just after 1 km of cutting length. It was found out through a DXR Raman microscope that similar to other classical brittle materials (silicon, germanium, etc.) an occurrence of brittle-ductile transition is responsible for the ductile-regime machining of 6H-SiC. It has also been demonstrated that the structural phase transformations associated with the diamond turning of brittle materials which are normally considered as a prerequisite to ductile-regime machining, may not be observed during ductile-regime machining of polycrystalline materials.

/pdf/brittle-ductile-transition-during-diamond-turning-of-single-4ou2nvzvpq.pdf

Brittle-ductile transition during diamond turning of single crystal silicon carbide

https://bura.brunel.ac.uk/bitstream/2438/1352/3/Paper-Cheng.pdf

Design of ultraprecision machine tools with applications to manufacture of miniature and micro components

Wear mechanism of diamond tools against single crystal silicon in single point diamond turning process

https://bura.brunel.ac.uk/bitstream/2438/1357/3/wompaper1-1.pdf

Xichun Luo

Papers

Diamond machining of silicon: A review of advances in molecular dynamics simulation

Brittle-ductile transition during diamond turning of single crystal silicon carbide

Design of ultraprecision machine tools with applications to manufacture of miniature and micro components

Wear mechanism of diamond tools against single crystal silicon in single point diamond turning process

Modeling and simulation of the tool wear in nanometric cutting